Template-Type: ReDIF-Article 1.0
Author-Name: Richard Alaimo
Author-X-Name-First: Richard
Author-X-Name-Last: Alaimo
Author-Name: Churlzu Lim
Author-X-Name-First: Churlzu
Author-X-Name-Last: Lim
Title: Compact MILP models for double row layout problem with pairwise clearance
Abstract:
Double row layout problem (DRLP) seeks for an optimal arrangement of departments along both sides of a central corridor to minimise the total material flow cost. This study considers a variant of DRLP where pairwise minimum clearance requirements between departments are enforced when they are assigned to the same side. This problem accounts for additional interaction that exists between departments during the layout planning process. Two mixed-integer linear programming formulations are proposed with the motivation that using fewer binary variables compared to the existing formulation in the literature helps reduce the solution time. Noting the NP-hardness of the problem, symmetry-breaking constraints are investigated in an effort to further alleviate the computational burden. The efficacy of the proposed models is demonstrated via a computational study using a set of test problem instances. [Received: 9 February 2022; Accepted: 11 August 2023]
Journal: European J. of Industrial Engineering
Pages: 45-67
Issue: 1
Volume: 19
Year: 2025
Keywords: facility layout; double row layout problem; mixed-integer linear programming; combinatorial optimisation; clearance requirements.
File-URL: http://www.inderscience.com/link.php?id=143080
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Handle: RePEc:ids:eujine:v:19:y:2025:i:1:p:45-67
Template-Type: ReDIF-Article 1.0
Author-Name: Letitia M. Pohl
Author-X-Name-First: Letitia M.
Author-X-Name-Last: Pohl
Author-Name: Mahmut Tutam
Author-X-Name-First: Mahmut
Author-X-Name-Last: Tutam
Title: Performance analysis for a dual-crane automated storage and retrieval system
Abstract:
Automated storage and retrieval systems (AS/RSs) were first implemented in the 1960s and continue to be installed today, albeit with dramatically evolved technologies. When compared to more manual systems, an AS/RS has the potential to dramatically reduce labour costs, with increased productivity, higher storage density, better order and inventory accuracy, and improved product security. Despite the advantages and widespread implementations, the typical unit-load, single-crane AS/RS is still often characterised by high initial costs and limited maximum throughput. This paper proposes a new design that uses two cranes in one aisle, where the cranes operate cooperatively to increase throughput, thereby allowing a facility that is at capacity to be retrofitted without a complete equipment upgrade and without the need for a new facility. We model travel time of the two cranes and develop system throughput equations. Significant throughput improvement is possible with the new design over a comparable single-crane AS/RS. [Received: 12 September 2022; Accepted 17 July 2023]
Journal: European J. of Industrial Engineering
Pages: 1-17
Issue: 1
Volume: 19
Year: 2025
Keywords: unit-load warehouse; automated storage and retrieval systems; AS/RS; dual-crane; optimal buffer position; throughput models.
File-URL: http://www.inderscience.com/link.php?id=143084
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Handle: RePEc:ids:eujine:v:19:y:2025:i:1:p:1-17
Template-Type: ReDIF-Article 1.0
Author-Name: Sudarshan Bardhan
Author-X-Name-First: Sudarshan
Author-X-Name-Last: Bardhan
Author-Name: Indrani Modak
Author-X-Name-First: Indrani
Author-X-Name-Last: Modak
Author-Name: Bibhas Chandra Giri
Author-X-Name-First: Bibhas Chandra
Author-X-Name-Last: Giri
Title: A multi-period inventory model with price, time and service level dependent demand under preservation technology investment
Abstract:
Price and time are two important parameters having significant impact on market demand, especially for fashion items, newly launched electronic products, etc. After-sale service facility offered by the retailers is seen to boost demand while investing in preservation technology reduces product spoilage. All these issues are taken into consideration while developing a multi-period inventory model where market demand depends on all three of the above-mentioned factors. The replenishment cycles are all of equal length, but due to the time-dependent nature of demand, the stock-in (and consequently stock-out) periods in the cycles are allowed to vary. The policy of planned shortages followed by replenishment in each cycle is adopted and seen to be fruitful indeed. Learning effect in holding and ordering costs are taken into account. The effects of limited capital and warehousing space are investigated. Numerical examples are employed to demonstrate the developed model and gain managerial insights from it. [Received: 23 December 2022; Accepted: 3 August 2023]
Journal: European J. of Industrial Engineering
Pages: 18-44
Issue: 1
Volume: 19
Year: 2025
Keywords: price dependent demand; learning effect; preservation technology; service level; multi-period inventory model.
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Handle: RePEc:ids:eujine:v:19:y:2025:i:1:p:18-44
Template-Type: ReDIF-Article 1.0
Author-Name: Chien-Wei Wu
Author-X-Name-First: Chien-Wei
Author-X-Name-Last: Wu
Author-Name: Ming-Hung Shu
Author-X-Name-First: Ming-Hung
Author-X-Name-Last: Shu
Author-Name: Bi-Min Hsu
Author-X-Name-First: Bi-Min
Author-X-Name-Last: Hsu
Author-Name: To-Cheng Wang
Author-X-Name-First: To-Cheng
Author-X-Name-Last: Wang
Title: Optimum design of an efficient variables sampling system for validating process yield with Six-Sigma quality requirement and creation of a cloud-computing too
Abstract:
Six Sigma quality levels have become well-known process yield targets in supply chain channels. To meet this high-yield requirement, the variables tightened-normal-tightened sampling system (VTSS) operates a dynamic rule-switching strategy between sampling plans, becoming a flexible and economical method for practitioners to verify products. Existing VTSSs based on the process yield index are only designed to adjust sample sizes in tightened and normal inspections. In this paper, a VTSS with alterable acceptance standards is developed. We derive the proposed VTSS's operating characteristic function and integrate it with the producer's and consumer's yield-and-risk requirements to construct an optimisation model for the determination of the optimal system design. After conducting a series of investigations into the performance between the proposed VTSS system with the existing VTSS system with alterable sample sizes, we concluded the proposed VTSS could reduce the average sample size by more than 50% and has a steeper operating characteristic shape, which indicates superior cost-efficiency and discriminative power. Moreover, we designed a cloud-computing tool to build an open-access platform to help practitioners implement our proposed VTSS easily and efficiently. Finally, the practicality and applicability of the proposed VTSS are illustrated through an industrial case. [Received: 15 December 2022; Accepted: 25 August 2023]
Journal: European J. of Industrial Engineering
Pages: 86-107
Issue: 1
Volume: 19
Year: 2025
Keywords: Six Sigma; process yield; lot sentencing; alterable acceptance standard ; tightened-normal-tightened sampling system.
File-URL: http://www.inderscience.com/link.php?id=143087
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Handle: RePEc:ids:eujine:v:19:y:2025:i:1:p:86-107
Template-Type: ReDIF-Article 1.0
Author-Name: Nadia Saeed
Author-X-Name-First: Nadia
Author-X-Name-Last: Saeed
Author-Name: Moustafa Omar Ahmed Abu-Shawiesh
Author-X-Name-First: Moustafa Omar Ahmed
Author-X-Name-Last: Abu-Shawiesh
Title: Sensitivity comparison of control charts under MAD shift detector using the rank set sampling scheme
Abstract:
In this article, the sensitivity comparison of the standard Shewhart <i>S</i>-control chart is done with the MAD-control chart under the rank set sampling (RSS) scheme. The median absolute deviation (MAD) from the sample median is considered a robust estimator for the outlier's detection relative to the sample standard deviation (SD). Extensive simulations are conducted to evaluate the control charts' performance using both estimators under the RSS scheme for different sample sizes. The values for the out-of-control average run length (<i>ARL</i><SUB align="right"><SMALL>1</SMALL></SUB>), standard deviation of run length (SDRL) and percentile points under different shifts are used as performance measures. On the basis of Monte Carlo simulations, it is revealed that as the shift gets large; control charts are equally effective to detect it while for small shifts, the suggested robust MAD-control chart performed well and better. A real-life dataset is analysed to support our findings from the simulation study for illustrative intents justified that the MAD robust estimator is a better outlier detector. [Received: 26 November 2022; Accepted: 11 August 2023]
Journal: European J. of Industrial Engineering
Pages: 68-85
Issue: 1
Volume: 19
Year: 2025
Keywords: rank set sampling; RSS; control chart; shift detector; outliers; median absolute deviation; MAD; percentile points; average run length; ARL.
File-URL: http://www.inderscience.com/link.php?id=143089
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Handle: RePEc:ids:eujine:v:19:y:2025:i:1:p:68-85
Template-Type: ReDIF-Article 1.0
Author-Name: Surendra Vikram Singh Padiyar
Author-X-Name-First: Surendra Vikram Singh
Author-X-Name-Last: Padiyar
Author-Name: Vandana Gupta
Author-X-Name-First: Vandana
Author-X-Name-Last: Gupta
Author-Name: Shiv Raj Singh
Author-X-Name-First: Shiv Raj
Author-X-Name-Last: Singh
Author-Name: Naveen Bhagat
Author-X-Name-First: Naveen
Author-X-Name-Last: Bhagat
Title: An EPQ model with different demand and deterioration rate for two warehouses under shortage, learning and imperfect production
Abstract:
This paper presents a mathematical framework to obtain a production model for deteriorating items with learning effect in production cost. The study considers different demand rates and different deterioration rate. In this model, one is own warehouse (OW) and other one is rented warehouse (RW) with different demand rate is considered. Every producer wants to get maximum benefit in his business, and he want to vacate the RW very soon, due to which he has to pay the least rent, so demand rate for RW is strictly increasing function of time. On the contrary, he can use his OW in such a way that the producer gets benefit and can build the selling price of inventory according to his profit, so demand rate for OW is selling price dependent. These assumptions effects on demand therefore production rate is taken as demand dependent. Shortage is also considered. Numerical example and sensitivity analysis of some parameters provided to examine the impact on the optimal total cost of the system. [Received: 28 January 2022; Accepted: 23 August 2023]
Journal: European J. of Industrial Engineering
Pages: 109-127
Issue: 2
Volume: 19
Year: 2025
Keywords: two warehouses; imperfect production; shortage; deterioration; learning effect.
File-URL: http://www.inderscience.com/link.php?id=144702
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Handle: RePEc:ids:eujine:v:19:y:2025:i:2:p:109-127
Template-Type: ReDIF-Article 1.0
Author-Name: Xiaohong Zhang
Author-X-Name-First: Xiaohong
Author-X-Name-Last: Zhang
Author-Name: Zhe Zhang
Author-X-Name-First: Zhe
Author-X-Name-Last: Zhang
Author-Name: Xiaoling Song
Author-X-Name-First: Xiaoling
Author-X-Name-Last: Song
Author-Name: Xiaofang Zhong
Author-X-Name-First: Xiaofang
Author-X-Name-Last: Zhong
Title: A hybrid approach of genetic algorithm and truncated branch-and-bound for seru scheduling problem with sequence-dependent setup time
Abstract:
This paper concentrates on the <i>seru</i> scheduling problem considering sequence-dependent setup time to minimise the makespan, in which <i>seru</i> production system (SPS) is a new-type advanced manufacturing system to respond quickly to volatile market. A mixed-integer programming (MIP) model is formulated, and then a hybridisation of genetic algorithm with a truncated branch-and-bound method (GATBB) is designed to speed up the solving process. Truncated branch-and-bound (TBB) procedure is employed to find a better solution than the initial one given by the GA within a tighter upper bound. Computational experiments are carried out finally, and a series of results of experiments, analyses of variance (ANOVA), and Tukey test show that the GATBB algorithm significantly outperforms the GA and GA-PSO algorithm. Specifically, GATBB algorithm performs extremely well in finding high-quality solutions efficiently, and can find approximate and even exact solutions for instances with up to 100 products. [Received: 31 October 2022; Accepted: 25 September 2023]
Journal: European J. of Industrial Engineering
Pages: 190-236
Issue: 2
Volume: 19
Year: 2025
Keywords: seru production system; setup times; scheduling; genetic algorithm; branch-and-bound.
File-URL: http://www.inderscience.com/link.php?id=144703
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Handle: RePEc:ids:eujine:v:19:y:2025:i:2:p:190-236
Template-Type: ReDIF-Article 1.0
Author-Name: James C. Chen
Author-X-Name-First: James C.
Author-X-Name-Last: Chen
Author-Name: Tzu-Li Chen
Author-X-Name-First: Tzu-Li
Author-X-Name-Last: Chen
Author-Name: Yin-Yann Chen
Author-X-Name-First: Yin-Yann
Author-X-Name-Last: Chen
Author-Name: Yung-Hsin Su
Author-X-Name-First: Yung-Hsin
Author-X-Name-Last: Su
Title: Applying a modified adaptive large neighbourhood search for truck scheduling and pile assignment in a two-stage sorting system
Abstract:
In this study, we tackle the complexities of a two-stage semi-automatic sorting system, considering the diverse distribution requirements of parcels and the constraints imposed by sorting equipment. Our objective is to integrate two decision points - the inbound truck schedule and the parcel sorting plan - to minimise overall operational costs. We first formulate the problem using a mixed-integer linear programming model and then propose a mixed-coded modified adaptive large neighbourhood search (MCMALNS) algorithm to enhance performance. In our computational study, the proposed approach demonstrated the ability to quickly obtain high-quality solutions compared to other algorithms. Furthermore, a full factorial experiment was conducted to analyse cost variations across 36 scenarios. Factors including loading, deadline, arrival pattern, pile/commodity ratio, and algorithm were all identified as significant and exhibited considerable influence on the outcomes. The insights derived from this analysis provide valuable guidance for management personnel in decision-making. [Received: 30 January 2023; Accepted: 25 August 2023]
Journal: European J. of Industrial Engineering
Pages: 128-161
Issue: 2
Volume: 19
Year: 2025
Keywords: truck scheduling; two-stage sorting system; modified adaptive large neighbourhood search.
File-URL: http://www.inderscience.com/link.php?id=144705
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Handle: RePEc:ids:eujine:v:19:y:2025:i:2:p:128-161
Template-Type: ReDIF-Article 1.0
Author-Name: Amit Ranjan
Author-X-Name-First: Amit
Author-X-Name-Last: Ranjan
Author-Name: Anand Ranjan
Author-X-Name-First: Anand
Author-X-Name-Last: Ranjan
Author-Name: J.K. Jha
Author-X-Name-First: J.K.
Author-X-Name-Last: Jha
Title: Pricing and greening strategies in a dual-channel supply chain with government tariffs and cannibalisation under demand uncertainty
Abstract:
In light of the drastic exhaustion of natural resources and increased environmental pollution, to promote the use of green products, the government subsidises them and levies taxes on non-green ones. This paper considers a dual-channel supply chain with a manufacturer selling a green product online and a substitutable non-green product offline using a retail channel. The price differential splits the market into two segments. The stochastic linear demand is modelled as a function of prices, green quality level, and sales effort level, considering government tariffs and demand leakage. A centralised decision model is investigated for the case of uniform distribution and distribution-free demand. It is shown that the green quality level and the total supply chain profit increase with an increase in demand leakage. Also, it reveals that with an increment in government subsidy and tax, the total supply chain profit and green quality level are higher in uniform distribution. [Received: 20 April 2023; Accepted: 9 October 2023]
Journal: European J. of Industrial Engineering
Pages: 237-271
Issue: 2
Volume: 19
Year: 2025
Keywords: dual-channel supply chain; government tariffs; cannibalisation; uniform distribution; distribution-free.
File-URL: http://www.inderscience.com/link.php?id=144706
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Handle: RePEc:ids:eujine:v:19:y:2025:i:2:p:237-271
Template-Type: ReDIF-Article 1.0
Author-Name: Özlem Akbudak
Author-X-Name-First: Özlem
Author-X-Name-Last: Akbudak
Author-Name: Gülşah Karakaya
Author-X-Name-First: Gülşah
Author-X-Name-Last: Karakaya
Author-Name: Meral Azizoğlu
Author-X-Name-First: Meral
Author-X-Name-Last: Azizoğlu
Title: Discrete time/cost trade-off project scheduling problem with tardiness bounds - an application to the Ministry of Health in Turkey
Abstract:
We consider a discrete time/cost trade-off problem with due dates and an upper bound on the total tardiness. Our motivation stems from information technology projects held in the Ministry of Health in Turkey. Our primary objective is to minimise the total cost while obeying the total tardiness bound. We formulate the problem as a mixed integer linear program and propose a heuristic approach that leverages the optimal solutions from the linear programming relaxation of the model. To assess the performances, we conduct tests on instances from relevant literature and the Ministry of Health projects, and report favourable results. We employ the optimal solutions to the constrained optimisation problem to generate the exact non-dominated objective vectors' set with respect to total tardiness and total cost. Additionally, we present an evolutionary algorithm to find an approximate set. The algorithms are demonstrated using the projects of the Ministry of Health in Turkey. [Received: 5 February 2023; Accepted: 10 September 2023]
Journal: European J. of Industrial Engineering
Pages: 162-189
Issue: 2
Volume: 19
Year: 2025
Keywords: discrete time/cost trade-off project scheduling problem; mixed integer linear program; heuristic approach; evolutionary algorithm.
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Handle: RePEc:ids:eujine:v:19:y:2025:i:2:p:162-189
Template-Type: ReDIF-Article 1.0
Author-Name: İzzettin Hakan Karaçizmeli
Author-X-Name-First: İzzettin Hakan
Author-X-Name-Last: Karaçizmeli
Title: Improving the quality of production through the Six Sigma method in a textile business
Abstract:
This study aims to reduce seam mark defects to improve the quality in a cotton fabric manufacture business by using the Six Sigma method. The DMAIC steps were followed. First, potential root causes were identified through brainstorming. Causes related to sewing thread, sewing machine settings and operator mistakes came to the fore in the brainstorming. Then, a data collection plan was devised, and the necessary data were collected. The analysis of studies on root causes were conducted by using the collected data. It was found that sewing thread, one of the raw materials used, played a role in increasing the defects. Furthermore, it was found that sewing operators needed training, and the settings of the machines should be improved. For solving these problems, the improvements were put into use. Finally, necessary monitoring plans were made. The results of the study indicated that the seam mark defects were reduced by 63%. [Received: 23 May 2023; Accepted: 16 October 2023]
Journal: European J. of Industrial Engineering
Pages: 295-312
Issue: 3
Volume: 19
Year: 2025
Keywords: quality; textile; Six Sigma; process improvement; seam mark.
File-URL: http://www.inderscience.com/link.php?id=145284
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Handle: RePEc:ids:eujine:v:19:y:2025:i:3:p:295-312
Template-Type: ReDIF-Article 1.0
Author-Name: Ruicheng Wang
Author-X-Name-First: Ruicheng
Author-X-Name-Last: Wang
Author-Name: Yue Xu
Author-X-Name-First: Yue
Author-X-Name-Last: Xu
Author-Name: Xiuli Wang
Author-X-Name-First: Xiuli
Author-X-Name-Last: Wang
Title: Shift scheduling and rostering with same shift-type and weekend-off fairness constraints in call centres
Abstract:
Based on the actual operational situation of call centres, this paper incorporates the constraints of the same shift-type within a week and the fairness of weekends-off into scheduling. Utilising the progressive decomposition structure of the same shift-type constraint, this paper constructs an integer programming model for multi-week scheduling optimisation problem of call centre agents. We first analyse the maximum lower bound of the problem and prove the optimality of its relaxation problem. Then we propose a two-stage algorithm which combines a constructive heuristic with neighbourhood search incorporating simulated annealing. Experimental results show that the integer programming model is only suitable for achieving optimal solutions for small-scale problems, while our two-stage algorithm can obtain (sub-)optimal solutions for large-scale problems. The impact of employment policy on labour costs is also discussed. [Received: 21 March 2023; Accepted: 12 November 2023]
Journal: European J. of Industrial Engineering
Pages: 340-373
Issue: 3
Volume: 19
Year: 2025
Keywords: call centre; shift scheduling; rostering; integer programming; optimal algorithm; heuristic algorithm; neighbourhood search; weekend-off fairness; same shift-type; operations management.
File-URL: http://www.inderscience.com/link.php?id=145292
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Handle: RePEc:ids:eujine:v:19:y:2025:i:3:p:340-373
Template-Type: ReDIF-Article 1.0
Author-Name: Salih O. Duffuaa
Author-X-Name-First: Salih O.
Author-X-Name-Last: Duffuaa
Author-Name: Omar Dehwah
Author-X-Name-First: Omar
Author-X-Name-Last: Dehwah
Author-Name: Abdul-Wahid Al-Saif
Author-X-Name-First: Abdul-Wahid
Author-X-Name-Last: Al-Saif
Author-Name: Anas Alghazi
Author-X-Name-First: Anas
Author-X-Name-Last: Alghazi
Author-Name: Awsan Mohammed
Author-X-Name-First: Awsan
Author-X-Name-Last: Mohammed
Title: A multi-objectives optimisation model for the joint design of statistical process control and engineering process control
Abstract:
Statistical process control and engineering process control are two methodologies used for process control and improvement. These technologies have existed independently of one another. Consequently, this research aims to simultaneously design statistical process control and engineering process control utilising multi-objectives optimisation. In this research, statistical and economic criteria are used to construct statistical process control and engineering process control jointly. To solve the developed model, an effective heuristic method is proposed. A numerical example is used to illustrate the significance of combining the two techniques. The results showed that the proposed solution could obtain the Pareto efficient solutions. This will help decision-makers to select the best solution based on their preferences. In addition, the findings indicated that the expected income values range between $172.0839 and $177.2175, and the Taguchi cost values vary between $4.469333 and $7.907547. On the other hand, the power values range between 0.91373 and 1. Moreover, the results revealed that as the Taguchi cost increases the expected income will increase and the power will decrease. Furthermore, sensitivity analysis is performed to determine the effect of variables in the model. The sensitivity analysis showed that the power of the chart decreases as the value of sigma is raised. [Received: 31 July 2023; Accepted: 26 November 2023]
Journal: European J. of Industrial Engineering
Pages: 374-399
Issue: 3
Volume: 19
Year: 2025
Keywords: statistical process control; SPC; engineering process control; EPC; multi-objectives; control charts; process monitoring.
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Handle: RePEc:ids:eujine:v:19:y:2025:i:3:p:374-399
Template-Type: ReDIF-Article 1.0
Author-Name: Mattia Neroni
Author-X-Name-First: Mattia
Author-X-Name-Last: Neroni
Author-Name: Javier Panadero
Author-X-Name-First: Javier
Author-X-Name-Last: Panadero
Author-Name: Elnaz Ghorbani
Author-X-Name-First: Elnaz
Author-X-Name-Last: Ghorbani
Author-Name: Majsa Ammouriova
Author-X-Name-First: Majsa
Author-X-Name-Last: Ammouriova
Author-Name: Angel A. Juan
Author-X-Name-First: Angel A.
Author-X-Name-Last: Juan
Title: An agile optimisation algorithm for the multi-source team orienteering problem
Abstract:
In the team orienteering problem (TOP), a fixed fleet of vehicles have to collect rewards by visiting customers. Typically, all vehicles depart from a source depot and end in a sink depot. Also, each vehicle has a limited driving range, so not all customers can be visited. The goal is then to select the set of customers to be visited, and the corresponding routes to do it, such in a way that the total reward collected is maximised while respecting the aforementioned constraints. This paper explores a TOP variant with multiple source depots and where real-time solutions need to be provided, i.e., computation times need to be in the order of milliseconds even for mid-sized instances with hundreds of customers. To deal with this challenge, and taking into account that the problem is <i>NP-hard</i>, we propose an 'agile' optimisation algorithm that is based on a biased-randomised heuristic. Our approach can be applied in realistic and dynamic scenarios where vehicles need to recompute their routes in real-time, as vehicles are in-route, new customers appear, and some existing customers are not available anymore. [Submitted: 20 May 2022; Accepted: 31 December 2022]
Journal: European J. of Industrial Engineering
Pages: 273-294
Issue: 3
Volume: 19
Year: 2025
Keywords: agile optimisation; biased-randomised heuristics; team orienteering problem; TOP; dynamic scenarios.
File-URL: http://www.inderscience.com/link.php?id=145302
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Handle: RePEc:ids:eujine:v:19:y:2025:i:3:p:273-294
Template-Type: ReDIF-Article 1.0
Author-Name: Jun Yao
Author-X-Name-First: Jun
Author-X-Name-Last: Yao
Author-Name: Dongyan Chen
Author-X-Name-First: Dongyan
Author-X-Name-Last: Chen
Author-Name: Hui Yu
Author-X-Name-First: Hui
Author-X-Name-Last: Yu
Title: Research on pricing strategy of closed-loop supply chain based on PIR and recovery effort
Abstract:
Waste products bring opportunities and challenges to remanufacturing. A Stackelberg game model based on PIR and recycling effort is constructed to compare and analyse the optimal pricing, product demand and system benefits of the closed-loop supply chain with or without PIR and recycling efforts. The results are as follows: compared with the without of PIR and recycling effort, manufacturers can lower the retail price of their products under PIR and recycling efforts to promote the increase of product demand and system total revenue. When the PIR level and the cost saving per unit of remanufactured product are constant, the larger the recycling amount of waste products is, the more total cost will be saved. It can be seen that recycling efforts will indirectly affect the level of PIR. When the input cost coefficient of PIR meets certain conditions, the manufacturer can obtain the income brought by PIR. [Received: 14 December 2022; Accepted: 7 November 2023]
Journal: European J. of Industrial Engineering
Pages: 313-339
Issue: 3
Volume: 19
Year: 2025
Keywords: process innovation for remanufacturing; PIR; recycling efforts; closed-loop supply chain; Stackelberg game; pricing strategy.
File-URL: http://www.inderscience.com/link.php?id=145304
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Handle: RePEc:ids:eujine:v:19:y:2025:i:3:p:313-339
Template-Type: ReDIF-Article 1.0
Author-Name: Mahdi Karimi
Author-X-Name-First: Mahdi
Author-X-Name-Last: Karimi
Author-Name: Seyed Jafar Sadjadi
Author-X-Name-First: Seyed Jafar
Author-X-Name-Last: Sadjadi
Title: Optimisation of a multi-item inventory model for deteriorating items with budget constraint, time-dependent holding costs, and two-level quantity discount: a comparison
Abstract:
Considering the increasing number of perishable goods, it is necessary to study the inventory control of these items. Previously, due to the difficulty of the models and the need for solution methods, many fundamental assumptions were ignored. This article presents a multi-item economic order quantity model for deteriorating items. This paper's novelties are using dynamic programming, adding both budget and capacity constraints, and some realistic assumptions to the model. This study allows shortages with partial backlogging, and a two-level discount is available. Also, we investigated the unspent budget elsewhere to increase the total income. The greedy search and metaheuristic methods were used to compare the results with the primary method. The results show that the proposed dynamic programming can solve the problem and surpass metaheuristic methods in precision and running time (for small cases). A sensitivity analysis was conducted and resulted in some managerial and theoretical insights. [Submitted: 19 June 2023; Accepted: 19 January 2024]
Journal: European J. of Industrial Engineering
Pages: 454-501
Issue: 4
Volume: 19
Year: 2025
Keywords: inventory control; economic order quantity; deteriorating items; budget constraint; capacity constraint; dynamic programming.
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Handle: RePEc:ids:eujine:v:19:y:2025:i:4:p:454-501
Template-Type: ReDIF-Article 1.0
Author-Name: Emine Akyol Özer
Author-X-Name-First: Emine Akyol
Author-X-Name-Last: Özer
Author-Name: Melis Alpaslan Takan
Author-X-Name-First: Melis Alpaslan
Author-X-Name-Last: Takan
Author-Name: Tuğba Saraç
Author-X-Name-First: Tuğba
Author-X-Name-Last: Saraç
Title: A mixed integer programming model and a hybrid VNS/TS algorithm for GVRP with the heterogeneous fleet, time windows, and vehicle selection
Abstract:
The green vehicle routing problem (GVRP) is a logistical problem considering environmental effects. Existing GVRP studies considered important constraints such as time windows (TW) or heterogeneous fleets (HF), but mostly, they assumed that there is an available fleet where all vehicles can be used. However, some companies build their fleets using rented cars by selecting the vehicle numbers and types. Therefore, we focus on GVRP with the HF, TW, and vehicle selection to minimise travel, rental, and emission costs. A MIP model, and a hybrid algorithm combining variable neighbourhood search with the tabu search algorithm are proposed. The performance of the algorithm is demonstrated by using the modified Solomon test instances. The proposed algorithm could produce high-quality solutions within a short computation time. In addition, an average improvement of 45.49% and 16.69% are achieved respectively compared to the first scenario and the second scenario where the vehicles are held constant. [Submitted: 6 February 2023; Accepted: 9 January 2024]
Journal: European J. of Industrial Engineering
Pages: 429-453
Issue: 4
Volume: 19
Year: 2025
Keywords: heterogeneous fleet green vehicle routing problem; HFGVRP; green vehicle routing problem with time window; GVRPTW; vehicle selection; variable neighbourhood search; VNS; tabu search; TS.
File-URL: http://www.inderscience.com/link.php?id=146501
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Handle: RePEc:ids:eujine:v:19:y:2025:i:4:p:429-453
Template-Type: ReDIF-Article 1.0
Author-Name: Guoli Liu
Author-X-Name-First: Guoli
Author-X-Name-Last: Liu
Title: Lagrangian-based solutions for the multi-level production-inventory problem in iron and steel production with reverse logistics
Abstract:
This research deals with the production-inventory problem originating from the ironmaking production system in Shanghai Baoshan Iron and Steel Complex. A mixed integer programming (MIP) model based on the minimisation of total related costs including production/purchasing costs, inventory costs and setup costs is proposed to determine the production and inventory quantities of all materials in each time period under material-balance and capacity constraints. To solve the problem, a decomposition approach based on Lagrangian relaxation (LR) is developed. A solution property is introduced to speed up the solving process. Heuristic strategies are applied to improve the upper bound. In order to further improve the quality of the solutions, an alternative Lagrangian relaxation algorithm based on variable splitting is derived. A detailed numerical evaluation based upon the actual production data from Baosteel is performed. The computational results reveal that the proposed algorithms can obtain good quality solutions within a reasonable time. [Submitted: 6 February 2023; Accepted: 25 February 2024]
Journal: European J. of Industrial Engineering
Pages: 502-538
Issue: 4
Volume: 19
Year: 2025
Keywords: combinatorial optimisation; Lagrangian relaxation; reverse logistics; production-inventory planning.
File-URL: http://www.inderscience.com/link.php?id=146503
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Handle: RePEc:ids:eujine:v:19:y:2025:i:4:p:502-538
Template-Type: ReDIF-Article 1.0
Author-Name: Qinyu Song
Author-X-Name-First: Qinyu
Author-X-Name-Last: Song
Author-Name: Meng Yang
Author-X-Name-First: Meng
Author-X-Name-Last: Yang
Author-Name: Yaodong Ni
Author-X-Name-First: Yaodong
Author-X-Name-Last: Ni
Title: Measuring modularity on manufacturers' distribution channel strategies: direct selling, reselling or agency selling
Abstract:
In recent years, consumers not only pursue cost-effective products but also begin to attach importance to individual customisation. This paper investigates the effects of the modularity level on a manufacturer's three channel strategies. We find that the modularity level under reselling and agency selling is lower than that under direct selling. Considering modularity, the retail price under agency selling is lower than that under direct selling. Therefore, when the consumer pays attention to the modular design, if the commission fee is high (low), the manufacturer will adopt the direct selling (agency selling) model. However, when the consumer's customisation concern is weak, the manufacturer prefers the reselling format. In addition, referring to dual distribution channels, the manufacturer may authorise the modular design to the retailer when the modular-sensitive the parameter is high. [Submitted: 29 August 2023; Accepted: 5 March 2024]
Journal: European J. of Industrial Engineering
Pages: 539-571
Issue: 4
Volume: 19
Year: 2025
Keywords: distribution channel; modularity; agency selling; reselling; game theory.
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Handle: RePEc:ids:eujine:v:19:y:2025:i:4:p:539-571
Template-Type: ReDIF-Article 1.0
Author-Name: Mahendra Saha
Author-X-Name-First: Mahendra
Author-X-Name-Last: Saha
Author-Name: Amartya Bhattacharya
Author-X-Name-First: Amartya
Author-X-Name-Last: Bhattacharya
Author-Name: Sukanta Pramanik
Author-X-Name-First: Sukanta
Author-X-Name-Last: Pramanik
Author-Name: Sudhansu S. Maiti
Author-X-Name-First: Sudhansu S.
Author-X-Name-Last: Maiti
Author-Name: Arindam Gupta
Author-X-Name-First: Arindam
Author-X-Name-Last: Gupta
Title: A unified generalised process capability index and its applications to logistic-exponential distributed characteristic
Abstract:
The introduction of the process capability index has made it possible for industries to evaluate process performance and assess how well the final product meets consumer expectations. In this article, we take into consideration the six most popular estimation techniques, namely the maximum likelihood, least square, weighted least square, percentile, Cramèr-von-Mises, and maximum product of spacing techniques, in order to estimate the parameters and the new unified measure of the generalised process capability index, denoted as <i>C<SUB align="right"><SMALL>py</SMALL></SUB></i> (<i>u</i>, <i>v</i>) for the logistic-exponential process distribution. Extensive simulations are carried out to investigate the performances of these considered classical estimation methods in terms of their respective biases and mean squared errors. Additionally, we contrast the results of three bootstrap confidence intervals of <i>C<SUB align="right"><SMALL>py</SMALL></SUB></i> (<i>u</i>, <i>v</i>) in terms of average widths and coverage probabilities: standard bootstrap, percentile bootstrap, and bias-corrected percentile bootstrap. Two datasets related to the electronic industries are re-analysed in order to show the applicability of the suggested methodologies. [Submitted: 28 December 2022; Accepted: 17 October 2023]
Journal: European J. of Industrial Engineering
Pages: 401-428
Issue: 4
Volume: 19
Year: 2025
Keywords: Monte-Carlo simulation; point and interval estimation; unified measure of process capability index.
File-URL: http://www.inderscience.com/link.php?id=146523
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Handle: RePEc:ids:eujine:v:19:y:2025:i:4:p:401-428
Template-Type: ReDIF-Article 1.0
Author-Name: Shuzhu Zhang
Author-X-Name-First: Shuzhu
Author-X-Name-Last: Zhang
Author-Name: Bingbing Qiu
Author-X-Name-First: Bingbing
Author-X-Name-Last: Qiu
Author-Name: Jinyue Tian
Author-X-Name-First: Jinyue
Author-X-Name-Last: Tian
Title: Design and development of an optimisation model and simheuristic framework for the on-demand delivery problem with driver-experience-based stochastic travel time
Abstract:
In this research, we investigate an on-demand delivery problem in city logistics, in which delivery requests from online customers are received in real-time and delivery services are conducted in short time. A multi-stage stochastic vehicle routing optimisation model is proposed, which incorporates two unique features arising from city logistics delivery, i.e., driver experience and stochastic travel time. In practice, the estimated travel time is indeed affected by the driver experience and can be gradually improved as drivers learn from accumulative delivery experience. A simheuristic framework is developed to handle the proposed model, in which an improved adaptive large neighbourhood search is designed for searching promising solutions with deterministic travel time, and Monte Carlo simulation is leveraged to assess the solution qualities and facilitate the searching process in stochastic scenarios. Computational experiments demonstrate that the proposed simheuristic framework can tackle the on-demand delivery problem with satisfactory performance. [Submitted: 22 November 2023; Accepted: 13 April 2024]
Journal: European J. of Industrial Engineering
Pages: 127-155
Issue: 1
Volume: 20
Year: 2025
Keywords: on-demand delivery; stochastic travel time; simheuristic framework; adaptive large neighbourhood search; driver experience.
File-URL: http://www.inderscience.com/link.php?id=147178
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Handle: RePEc:ids:eujine:v:20:y:2025:i:1:p:127-155
Template-Type: ReDIF-Article 1.0
Author-Name: Bahareh Sohrabi Pirdousti
Author-X-Name-First: Bahareh Sohrabi
Author-X-Name-Last: Pirdousti
Author-Name: Amir Hossein Sheikh Azadi
Author-X-Name-First: Amir Hossein Sheikh
Author-X-Name-Last: Azadi
Author-Name: Ali Heidari
Author-X-Name-First: Ali
Author-X-Name-Last: Heidari
Author-Name: Mohammad Khalilzadeh
Author-X-Name-First: Mohammad
Author-X-Name-Last: Khalilzadeh
Author-Name: Omid Kebriyaii
Author-X-Name-First: Omid
Author-X-Name-Last: Kebriyaii
Title: A sustainable hub location-allocation model considering the inspection of defective wagons in the rail freight network
Abstract:
The increasing demand for rail transport necessitates an effective transportation network design for the shipment of goods with minimum cost and time. Since the breakdown of wagons is a main delay factor in rail transportation, the maintenance and repairs of defective wagons becomes prominent. In this study, main stations are considered as hubs, and hubs are places where defective wagons are collected. For this purpose, a robust multi-objective mathematical model is proposed to minimise transportation costs considering customer demand. Also, the model seeks to minimise the total transportation time and emissions. The AEC method is exploited to solve and validate the proposed model. Moreover, the sensitivity analysis is performed to demonstrate the effect of changing the main parameters on the outcomes. The results show that repairs and maintenance can affect the capacity. Also, the findings demonstrate the applicability and validity of the proposed model in the railway sector. [Submitted: 29 May 2023; Accepted: 16 January 2024]
Journal: European J. of Industrial Engineering
Pages: 94-126
Issue: 1
Volume: 20
Year: 2025
Keywords: railway transportation; sustainability; hub location-allocation; maintenance; repair; augmented epsilon constraint; AEC.
File-URL: http://www.inderscience.com/link.php?id=147183
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Handle: RePEc:ids:eujine:v:20:y:2025:i:1:p:94-126
Template-Type: ReDIF-Article 1.0
Author-Name: Alireza Hamidieh
Author-X-Name-First: Alireza
Author-X-Name-Last: Hamidieh
Author-Name: Bahareh Akhgari
Author-X-Name-First: Bahareh
Author-X-Name-Last: Akhgari
Title: Designing a reverse biomass supply chain network under uncertainty conditions using robust programming and Lagrangian relaxation algorithm
Abstract:
Researchers have studied solutions for reducing pollution and resource waste caused by increases in environmental pollution and resource waste. Moreover, increased productivity, reduced energy generation costs, decreased dependence on fossil fuels and use of biogas in supply chain networks have attracted interest from many industrialists. This research designed a biomass-based reverse supply chain network under conditions of uncertainty about capacity, demand and raw material quality that focused on increased profits and reduced biomass waste. For this purpose, a two-stage stochastic mixed-integer programming model was developed and robust optimisation was used to cope with the uncertainty about the parameters of quality, demand and capacity. In addition, a Lagrangian relaxation (LR) algorithm for simplification of the complicated constraints of the NP-hard problem was developed that could solve large-scale problems with a competitive convergence rate. [Submitted: 6 July 2022; Accepted; 4 December 2023]
Journal: European J. of Industrial Engineering
Pages: 32-56
Issue: 1
Volume: 20
Year: 2025
Keywords: biomass; Lagrangian relaxation; quality; robust; supply chain.
File-URL: http://www.inderscience.com/link.php?id=147184
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Handle: RePEc:ids:eujine:v:20:y:2025:i:1:p:32-56
Template-Type: ReDIF-Article 1.0
Author-Name: Chen Fung Liew
Author-X-Name-First: Chen Fung
Author-X-Name-Last: Liew
Author-Name: Joshua Prakash
Author-X-Name-First: Joshua
Author-X-Name-Last: Prakash
Author-Name: Kok Seng Ong
Author-X-Name-First: Kok Seng
Author-X-Name-Last: Ong
Title: Assessment of equipment financial performance in overall equipment effectiveness metric for gauging manufacturing equipment criticality
Abstract:
This paper introduces equipment cost effectiveness, a metric for evaluating the financial performance of equipment in manufacturing. While overall equipment effectiveness is widely used to assess operational performance, its limited focus on financial aspects necessitates a more comprehensive approach. Equipment cost effectiveness addresses this limitation by quantifying the wastage of equipment acquisition cost and maintenance cost at any overall equipment effectiveness level. Real-world data from the medical device, tyre flap, and semiconductor industries validate equipment cost effectiveness through correlation analysis, revealing a negative relationship between overall equipment effectiveness and both equipment acquisition cost and maintenance cost. Equipment cost effectiveness provides a holistic evaluation of equipment, enabling better decision-making and cost optimisation. By bridging the gap between operational and financial evaluations, equipment cost effectiveness offers valuable insights for enhancing equipment efficiency and resource allocation in manufacturing operations. [Submitted: 22 April 2023; Accepted: 10 November 2023]
Journal: European J. of Industrial Engineering
Pages: 1-31
Issue: 1
Volume: 20
Year: 2025
Keywords: overall equipment effectiveness; OEE; equipment cost effectiveness; ECE; equipment acquisition cost; maintenance cost; improvement cost.
File-URL: http://www.inderscience.com/link.php?id=147185
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Handle: RePEc:ids:eujine:v:20:y:2025:i:1:p:1-31
Template-Type: ReDIF-Article 1.0
Author-Name: Xiaoqing Zhang
Author-X-Name-First: Xiaoqing
Author-X-Name-Last: Zhang
Author-Name: Xigang Yuan
Author-X-Name-First: Xigang
Author-X-Name-Last: Yuan
Author-Name: Yongjian Wang
Author-X-Name-First: Yongjian
Author-X-Name-Last: Wang
Author-Name: Dalin Zhang
Author-X-Name-First: Dalin
Author-X-Name-Last: Zhang
Title: Dual-channel selection strategy of green supply chain considering online retail platform under different forms of government subsidies
Abstract:
To accelerate the sustainable development of green supply chains (GSCs), governments adopt different forms of subsidies, including research and development (R%D) cost subsidies and unit production subsidies, and manufacturers develop different dual-channel structure models based on these subsidies. We build one three-level game analysis model including a government, a manufacturer, and an online retail platform and solve it using the backward induction method, and we explore the optimal dual-channel structure model of GSCs. We find that when the manufacturer better controls the cost of green R%D, the unit production subsidy is better for producing green products and can also make the online retail platform more profitable. When the government offers the R%D cost subsidy, the manufacturer should select the online direct and online reselling channel structure model. In contrast, when offering the unit production subsidy, the manufacturer should adopt the online direct and online reselling channel structure model under certain conditions. Furthermore, when both the cost ratio of technology R%D and the marginal revenue rate of environmental improvement are lower than a certain threshold, the unit production subsidy is a better strategy for the government. Otherwise, we suggest that the government adopt an R%D cost subsidy strategy. [Submitted: 30 November 2022; Accepted: 27 December 2023]
Journal: European J. of Industrial Engineering
Pages: 57-93
Issue: 1
Volume: 20
Year: 2025
Keywords: green supply chain; GSC; government subsidy; online direct channel; online reselling channel; online agency channel.
File-URL: http://www.inderscience.com/link.php?id=147192
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Handle: RePEc:ids:eujine:v:20:y:2025:i:1:p:57-93
Template-Type: ReDIF-Article 1.0
Author-Name: Armin Darmawan
Author-X-Name-First: Armin
Author-X-Name-Last: Darmawan
Author-Name: Chien-Wei Wu
Author-X-Name-First: Chien-Wei
Author-X-Name-Last: Wu
Title: Designing an enhanced acceptance sampling strategy with the process loss index
Abstract:
To reconcile the differences between loose and stringent models and address product specifications sensitive to target value variations, a process loss index <i>L<SUB align="right"><SMALL>e</SMALL></SUB></i> was introduced. This index assesses process capability by incorporating the concept of the quality loss function. Some researchers have integrated this index into variables sampling plans. In particular, Repetitive Group Sampling Plans (RGSP) offer cost advantages over single sampling plans, but their infinite sampling nature might lead to inefficiencies. To address this, our study introduces a modified RGSP with an adjustable lot disposition mechanism based on the process loss index. We establish an optimisation model to minimise the anticipated number of sample items, considering quality and risk constraints. Performance is compared to conventional methods using metrics such as average sample number, operating characteristic curve, and average run length. Ultimately, a practical demonstration is provided through an example to illustrate and validate the feasibility of the proposed plan. [Submitted: 22 January 2024; Accepted: 17 May 2024]
Journal: European J. of Industrial Engineering
Pages: 157-182
Issue: 2
Volume: 20
Year: 2025
Keywords: acceptance sampling; average sample number; quality loss; quality assurance; operating characteristic function.
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Handle: RePEc:ids:eujine:v:20:y:2025:i:2:p:157-182
Template-Type: ReDIF-Article 1.0
Author-Name: Davide Castellano
Author-X-Name-First: Davide
Author-X-Name-Last: Castellano
Author-Name: Mosè Gallo
Author-X-Name-First: Mosè
Author-X-Name-Last: Gallo
Title: Integrated assortment, shelf space and inventory decisions in retail considering product deterioration with elasticity and positioning effects
Abstract:
This paper investigates a problem faced by retailers when selling multiple products and specifically the decisions related to product assortment, shelf-space planning, inventory replenishment, and storage capacity allocation. Products deteriorate while in stock and are jointly replenished. Additionally, their demand is influenced by elasticity and positioning effects. The retailer's objective is to maximise the profit by determining the optimal ratio between the surfaces assigned to the backroom facility and the display area, the optimal product assortment, the optimal space assignment and allocation, and the optimal coordinated inventory replenishment policy. A hybrid solution procedure, including a genetic algorithm, is proposed. Among the findings, it was observed that as the decay rate increases, it is preferable to reduce the surface dedicated to the backroom facility. In fact, to mitigate the negative impact of deterioration on profit, it appears desirable to reduce the order quantity and expand the product assortment. [Submitted: 16 January 2024; Accepted: 29 July 2024]
Journal: European J. of Industrial Engineering
Pages: 278-315
Issue: 2
Volume: 20
Year: 2025
Keywords: inventory; deterioration; assortment; shelf space; optimisation; retail.
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Handle: RePEc:ids:eujine:v:20:y:2025:i:2:p:278-315
Template-Type: ReDIF-Article 1.0
Author-Name: Andro Dragović
Author-X-Name-First: Andro
Author-X-Name-Last: Dragović
Author-Name: Nenad Zrnić
Author-X-Name-First: Nenad
Author-X-Name-Last: Zrnić
Author-Name: Branislav Dragović
Author-X-Name-First: Branislav
Author-X-Name-Last: Dragović
Author-Name: Maxim A. Dulebenets
Author-X-Name-First: Maxim A.
Author-X-Name-Last: Dulebenets
Title: Exploring the role of influential scholars in maritime and port logistics systems
Abstract:
There is no annual ranking for top scientists in the area of maritime and port logistics systems (MPLSs), such as in the area of physics or top 10 most influential mathematicians. Therefore, the main aims of the present study are to offer the academic community more visibility of the influential research and highlight the scholars whose relevant bibliometric indexes are higher than average. A systematic, scientific, and fair approach based on very well-known bibliometric indexes is conducted to identify the most influential scholars. This provides possibilities for a rigorous comparative analysis, as well as assessment of scholars' scientific outputs. The internal database includes a total of 8,774 documents that were comprehensively analysed. All the obtained results are reproducible and verifiable. If this approach omitted some credible scholars, it should not be considered as a judgment of the merit of their scientific output. [Submitted: 14 February 2024; Accepted: 15 July 2024]
Journal: European J. of Industrial Engineering
Pages: 216-250
Issue: 2
Volume: 20
Year: 2025
Keywords: influential scholars; scientific output; word cloud analysis; conceptual structure analysis.
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Handle: RePEc:ids:eujine:v:20:y:2025:i:2:p:216-250
Template-Type: ReDIF-Article 1.0
Author-Name: Parvaneh Zeraati Foukolaei
Author-X-Name-First: Parvaneh Zeraati
Author-X-Name-Last: Foukolaei
Title: Two-stage stochastic robust programming based on MOPSSCA for flight crew scheduling problem
Abstract:
The main purpose of providing the mathematical model is to achieve the optimal flight schedule, optimal fleet allocation, optimal aircraft routing, and crew scheduling to reduce the total costs of flights and the amount of fuel consumed in all flights. Due to the uncertainty of the flight of the planes at the appointed time and the presence of numerous delays, modelling in different scenarios was presented based on the probability of the event. The calculation results of solving the numerical example with the epsilon method of the limit showed that the change in the flight schedule of the planes and the presence of delay in it leads to an increase in the flight costs and, as a result, leads to an increase in the amount of fuel consumed. In this article, a new hybrid algorithm named MOPSSCA was introduced, which has achieved near-optimal solutions with a maximum error of 2%. [Submitted: 12 December 2023; Accepted: 29 July 2024]
Journal: European J. of Industrial Engineering
Pages: 251-277
Issue: 2
Volume: 20
Year: 2025
Keywords: flight crew scheduling; two-stage stochastic robust programming; MOPSSCA; crew scheduling; flight routing.
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Handle: RePEc:ids:eujine:v:20:y:2025:i:2:p:251-277
Template-Type: ReDIF-Article 1.0
Author-Name: Yanjie Zhou
Author-X-Name-First: Yanjie
Author-X-Name-Last: Zhou
Author-Name: Liping Luo
Author-X-Name-First: Liping
Author-X-Name-Last: Luo
Author-Name: Qian Qian Zhao
Author-X-Name-First: Qian Qian
Author-X-Name-Last: Zhao
Author-Name: Haonan Chen
Author-X-Name-First: Haonan
Author-X-Name-Last: Chen
Author-Name: Zehao Qian
Author-X-Name-First: Zehao
Author-X-Name-Last: Qian
Author-Name: Songle Leng
Author-X-Name-First: Songle
Author-X-Name-Last: Leng
Title: Influence index analysis of inland waterway ports along the Yangtze River
Abstract:
The port performance index is an essential parameter for evaluating the performance of container ports and port selection. Many previous studies have investigated the methods of port performance index for seaports and focused on annual data analysis. Inland waterway ports located along the inland waterway have different functions compared with seaports that cannot use the previous method adopted for seaports to calculate the inland port influence index. To make a comprehensive analysis, this paper considers multiple years' worth of factors, including the facility of inland ports, urban economic and traffic factors. This paper introduces a group entropy weight method to evaluate the inland port influence index considering the multiple year data. A visualisation tool integrated with the group entropy weight method is developed to analyse the port performance index automatically. Twenty-seven inland waterway ports along the Yangtze River are considered as a case study for analysing their influence index. The management insights of the dynamic change of inland waterway port ranks are also discussed. [Submitted: 4 March 2024; Accepted: 28 June 2024]
Journal: European J. of Industrial Engineering
Pages: 183-215
Issue: 2
Volume: 20
Year: 2025
Keywords: port performance index; Yangtze River; inland waterway ports; port ranking.
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Handle: RePEc:ids:eujine:v:20:y:2025:i:2:p:183-215
Template-Type: ReDIF-Article 1.0
Author-Name: N. Firoz
Author-X-Name-First: N.
Author-X-Name-Last: Firoz
Author-Name: Vinay V. Panicker
Author-X-Name-First: Vinay V.
Author-X-Name-Last: Panicker
Title: Strategic insights: a system dynamics approach to analyse sustainability and cost efficiency in Indian freight transportation scenarios
Abstract:
Freight transportation decarbonising is one of the key challenges in climate change mitigation efforts. The modal shift is considered a widely accepted effective strategy towards reducing carbon emissions in transportation. The main focus of this paper is to analyse the modal shift policy towards freight transport decarbonisation in India. A carbon tax on road transport was proposed to promote the transport to low carbon transport modes. A system dynamics model was developed to analyse the time-dependent complex freight transportation system with the introduction of a carbon tax under three scenarios. The optimal modal share can be obtained in a fast-change scenario by 2042, with a significant reduction of 37% in carbon emission and 4% in logistics cost. The fast change scenario recommends the modal transition at a rate of 1-1.5%. These findings will support the government for proactive measures for a swift transition in line with the fast-change scenario. [Submitted: 12 October 2023; Accepted: 6 August 2024]
Journal: European J. of Industrial Engineering
Pages: 335-367
Issue: 3
Volume: 20
Year: 2025
Keywords: freight transport; decarbonisation; modal shift; carbon tax; system dynamics; India.
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Handle: RePEc:ids:eujine:v:20:y:2025:i:3:p:335-367
Template-Type: ReDIF-Article 1.0
Author-Name: Weichen Gao
Author-X-Name-First: Weichen
Author-X-Name-Last: Gao
Author-Name: Shanhua Wu
Author-X-Name-First: Shanhua
Author-X-Name-Last: Wu
Author-Name: Hongxiang Feng
Author-X-Name-First: Hongxiang
Author-X-Name-Last: Feng
Author-Name: Zhongzhen Yang
Author-X-Name-First: Zhongzhen
Author-X-Name-Last: Yang
Title: Optimisation of the length of global supply chain for decarbon purpose
Abstract:
Economic globalisation has boosted production and consumption, improving living standards but increasing demand for long distance trade transportation and carbon emissions. This paper maps global export cargo turnover as the length of the global supply chain (SCL) and introduces a method to calculate each country's carbon emissions based on consumer responsibility. The method considers emissions from manufacturing, transportation and technological disparities of finished goods between countries. To minimise total costs, including carbon costs, we optimise the SCL. Empirical analysis of by taking China, the USA, Japan, European Union and ASEAN as a small and closed area shows a 43.69% reduction in optimised SCL. The USA contributes 59.31% of this reduction, 8.5 times that of China and 18 times that of ASEAN. Under this optimisation, total carbon emissions from manufacturing will drop by 6.62%, with China experiencing the largest decrease (25.23%) and the USA the largest increase (15.91%). [Submitted: 24 February 2024; Accepted: 4 September 2024]
Journal: European J. of Industrial Engineering
Pages: 448-476
Issue: 3
Volume: 20
Year: 2025
Keywords: global supply chain; economic globalisation; international trade transportation; carbon emissions; finished goods.
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Handle: RePEc:ids:eujine:v:20:y:2025:i:3:p:448-476
Template-Type: ReDIF-Article 1.0
Author-Name: Yueran Zhang
Author-X-Name-First: Yueran
Author-X-Name-Last: Zhang
Author-Name: Zhanwen Niu
Author-X-Name-First: Zhanwen
Author-X-Name-Last: Niu
Author-Name: Kaixuan Hou
Author-X-Name-First: Kaixuan
Author-X-Name-Last: Hou
Title: Simulation-based ripple effect modelling in the supply chain: a network perspective
Abstract:
This research investigates the ripple effects of supply chain disruptions across supply chain echelons and identifies vulnerable network characteristics. Utilising simulation methods, the study analyses the impact of disruption scale, propagation extent, and delay on supply chain performance. Employing AnyLogistix software, the study evaluates ripple effects across four different network structures under disruption scenarios resembling the COVID-19 pandemic, characterised by prolonged impacts on supply, demand, logistics, and uncertain recovery times. Comparative analysis across network structures reveals insights into recovery strategies, highlighting the influence of network characteristics on performance outcomes. The findings demonstrate that both disruption severity and propagation delay significantly affect supply chain performance, with high connectivity and betweenness centrality enhancing resilience during prolonged disruptions. This study contributes to the literature by integrating ripple effect assessment with network topology considerations, providing both theoretical insights and practical guidance for optimising supply chain design and management in the post-COVID era. [Submitted: 8 February 2024; Accepted: 3 September 2024]
Journal: European J. of Industrial Engineering
Pages: 368-410
Issue: 3
Volume: 20
Year: 2025
Keywords: disruption; ripple effect; supply chain; simulation; resilience; network structure; network characteristics.
File-URL: http://www.inderscience.com/link.php?id=148090
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Handle: RePEc:ids:eujine:v:20:y:2025:i:3:p:368-410
Template-Type: ReDIF-Article 1.0
Author-Name: Tien-Yu Lin
Author-X-Name-First: Tien-Yu
Author-X-Name-Last: Lin
Title: Optimising logistics packaging and replenishing policies for deteriorating items in e-commerce environments
Abstract:
This paper develops an instantaneously deteriorating inventory model for an e-commerce environment wherein the retailer employs an improved logistics packaging policy to reduce the rate of damage to goods in transit. Because of the difficulty in finding a closed-form solution, an efficient algorithm has been developed to find the optimal solution for the proposed model. The theoretical results show that the deteriorating rate could impact the optimal solution and the average total profit. The replenishment time for the proposed model with return rate is shorter than that for the traditional EOQ model. Numerical examples illustrate the proposed model and algorithm. Moreover, sensitivity analysis illustrates the effects of four parameters of importance (i.e., set-up cost, demand rate, holding cost, and deteriorating rate) on the optimal strategy. The discussion of numerical and sensitivity analysis results provide some managerial insights. [Submitted: 6 June 2023; Accepted: 15 February 2024]
Journal: European J. of Industrial Engineering
Pages: 317-334
Issue: 3
Volume: 20
Year: 2025
Keywords: inventory; logistics packing policy; deterioration; e-commerce; replenishing policy.
File-URL: http://www.inderscience.com/link.php?id=148092
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Handle: RePEc:ids:eujine:v:20:y:2025:i:3:p:317-334
Template-Type: ReDIF-Article 1.0
Author-Name: Ageel Alogla
Author-X-Name-First: Ageel
Author-X-Name-Last: Alogla
Author-Name: Martin Baumers
Author-X-Name-First: Martin
Author-X-Name-Last: Baumers
Author-Name: Christopher Tuck
Author-X-Name-First: Christopher
Author-X-Name-Last: Tuck
Title: Characterising the cost of additive manufacturing: demand volatility and absence of inventory
Abstract:
This paper explores the impact of additive manufacturing (AM) on supply chain cost-effectiveness for products with volatile demand. It specifically assesses how AM adoption affects inventory and stockout costs through an exploratory simulation. The study compares the unit costs of AM with injection moulding (IM) and a combination of both. Results indicate that using AM alongside IM is cost-effective only with high stockout penalties. Without such penalties, IM alone proves to be the most economical option. This research provides insights into strategic production decisions in supply chains with fluctuating demand. [Submitted: 13 December 2023; Accepted: 4 September 2024]
Journal: European J. of Industrial Engineering
Pages: 411-447
Issue: 3
Volume: 20
Year: 2025
Keywords: advanced manufacturing technology; discrete-event simulation; demand uncertainty; design of production systems; bullwhip effect.
File-URL: http://www.inderscience.com/link.php?id=148094
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Handle: RePEc:ids:eujine:v:20:y:2025:i:3:p:411-447
Template-Type: ReDIF-Article 1.0
Author-Name: Deling Yuan
Author-X-Name-First: Deling
Author-X-Name-Last: Yuan
Author-Name: Zexi Yang
Author-X-Name-First: Zexi
Author-X-Name-Last: Yang
Title: A hybrid particle swarm optimisation algorithm for multi-resource constrained flexible job shop scheduling problem with transportation
Abstract:
In the flexible job processing environment, there exists an insufficient optimisation of spatial and transportation resources. To effectively solve the multi-resource constrained flexible job shop scheduling problem with transportation, it is imperative to consider factors such as the capacity of transportation equipment, limitations of the transportation equipment temporary storage area and job temporary storage area. This article focuses on the coordinated scheduling of processing and transportation tasks, aiming to minimise the makespan and the total equipment running time. A hybrid particle swarm optimisation algorithm (NHPSO) is designed, incorporating genetic algorithm's (GA) crossover and mutation functions to preserve particles' genetic information while enhancing global search capabilities. The simulated annealing (SA) mechanism is also included to boost early-to-mid-stage optimisation ability and broaden solution search range. A neighbourhood search strategy based on the critical chain concept is developed in three evolutionary directions to enhance algorithm effectiveness without getting stuck at local optimums. Finally, the convergence ability and effectiveness of the proposed algorithm are verified by experiments. [Submitted: 4 November 2023; Accepted: 20 July 2024]
Journal: European J. of Industrial Engineering
Pages: 477-513
Issue: 4
Volume: 20
Year: 2025
Keywords: flexible job shop scheduling; FJSP; limited resources; particle swarm optimisation; neighbourhood search; transportation.
File-URL: http://www.inderscience.com/link.php?id=149834
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Handle: RePEc:ids:eujine:v:20:y:2025:i:4:p:477-513
Template-Type: ReDIF-Article 1.0
Author-Name: Kooi Huat Ng
Author-X-Name-First: Kooi Huat
Author-X-Name-Last: Ng
Author-Name: Chan Hoong Lee
Author-X-Name-First: Chan Hoong
Author-X-Name-Last: Lee
Author-Name: Jeng Young Liew
Author-X-Name-First: Jeng Young
Author-X-Name-Last: Liew
Author-Name: Kok Haur Ng
Author-X-Name-First: Kok Haur
Author-X-Name-Last: Ng
Author-Name: Yann Ling Goh
Author-X-Name-First: Yann Ling
Author-X-Name-Last: Goh
Title: Robust monitoring of contaminated data in detecting the change point with the Shewhart mean chart
Abstract:
The Shewhart mean (<i>X̄</i>) chart is a powerful device for distinguishing special cause variations. The change point is often slower than the <i>X̄</i> chart's signalling time in practice. Knowing the actual process change time reduces the opportunity window for locating the special cause. This paper exploits the robust monitoring of contaminated data concerning the <i>X̄</i> chart's change point detection. The estimated expected run lengths, average change point estimates, and related standard errors of change point estimates for different process shifts under various contamination percentages are computed using Monte Carlo simulation to assess the <i>X̄</i> chart's performance. The findings reveal that the average estimated process change time with its corresponding standard error of estimate declines proportionally when the contamination percentage increases. In contrast, the expected run length increases proportionally when several contamination levels occur, hinting that the <i>X̄</i> chart's process shift detection efficiency decreases with an increase in contamination. [Submitted: 27 November 2023; Accepted: 6 October 2024]
Journal: European J. of Industrial Engineering
Pages: 550-568
Issue: 4
Volume: 20
Year: 2025
Keywords: Shewhart mean chart; change point; robust; contamination; expected run length.
File-URL: http://www.inderscience.com/link.php?id=149840
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Handle: RePEc:ids:eujine:v:20:y:2025:i:4:p:550-568
Template-Type: ReDIF-Article 1.0
Author-Name: Stefan Mišković
Author-X-Name-First: Stefan
Author-X-Name-Last: Mišković
Author-Name: Olivera Stančić
Author-X-Name-First: Olivera
Author-X-Name-Last: Stančić
Author-Name: Zorica Stanimirović
Author-X-Name-First: Zorica
Author-X-Name-Last: Stanimirović
Author-Name: Raca Todosijević
Author-X-Name-First: Raca
Author-X-Name-Last: Todosijević
Title: Multi-level uncapacitated facility location problem with clients' preferences
Abstract:
This paper introduces the multi-level uncapacitated facility location problem with clients' preferences (MLUFLP-CP), which represents a generalisation of the well-known multi-level uncapacitated facility location problem (MLUFLP). The MLUFLP-CP is first modelled as a bi-level mathematical program, and then reformulated into four equivalent integer linear programs. Due to the NP-hardness of the MLUFLP-CP, the problem instances of real-world dimensions are unsolved to optimality by CPLEX solver. Therefore, we have designed a general variable neighbourhood search (GVNS) metaheuristic as an efficient solution approach to the MLUFLP-CP. The GVNS concept and its parameters are adapted to the multi-level nature of problem, and a novel VND variant, denoted as multi-level VND, is used as a local search improvement procedure. Computational experiments on MLUFLP-CP instances show that the proposed GVNS quickly reaches all known optimal solutions, improves upper bounds obtained by CPLEX and efficiently provides solutions for large-scale instances that were out of reach for CPLEX. [Submitted: 29 March 2024; Accepted: 4 December 2024]
Journal: European J. of Industrial Engineering
Pages: 569-589
Issue: 4
Volume: 20
Year: 2025
Keywords: multi-level facility location problem; clients' preferences; bi-level mathematical program; integer linear programming; CPLEX solver; variable neighbourhood search; VNS; variable neighbourhood descent; VND.
File-URL: http://www.inderscience.com/link.php?id=149843
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Handle: RePEc:ids:eujine:v:20:y:2025:i:4:p:569-589
Template-Type: ReDIF-Article 1.0
Author-Name: Qing-Mi Hu
Author-X-Name-First: Qing-Mi
Author-X-Name-Last: Hu
Author-Name: Shihao Guo
Author-X-Name-First: Shihao
Author-X-Name-Last: Guo
Title: Design of incomplete hub location-routing networks in an intra-city metro logistics system
Abstract:
This paper addresses the design of incomplete hub location-routing networks in an intra-city metro logistics system, in which flows of mail and parcels are exchanged among customers via the integrated ground road and underground metro transport modes. The network design is modelled as a two-stage optimisation decision. In the first stage, candidate hubs are determined by an improved K-means clustering algorithm and the E-TOPSIS model. In the second stage, a mixed-integer programming formulation is proposed to determine hub locations, demand allocation, metro route selection, and ground distribution routes. Moreover, to tackle large-scale instances, a hybrid heuristic algorithm based on Tabu search and adaptive large neighbourhood search is proposed, and extensive numerical experiments with randomly generated instances are conducted to validate the effectiveness of model and algorithm. Finally, we present a realistic case study on the Shanghai metro in China, and analyse the impact of different parameters on network configurations. [Submitted: 17 June 2024; Accepted: 4 December 2024]
Journal: European J. of Industrial Engineering
Pages: 590-652
Issue: 4
Volume: 20
Year: 2025
Keywords: incomplete hub location-routing; intra-city metro logistics; E-TOPSIS model; mixed-integer programming; hybrid heuristics.
File-URL: http://www.inderscience.com/link.php?id=149844
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Handle: RePEc:ids:eujine:v:20:y:2025:i:4:p:590-652
Template-Type: ReDIF-Article 1.0
Author-Name: Mengdie Huang
Author-X-Name-First: Mengdie
Author-X-Name-Last: Huang
Author-Name: Tangbin Xia
Author-X-Name-First: Tangbin
Author-X-Name-Last: Xia
Author-Name: Guojin Si
Author-X-Name-First: Guojin
Author-X-Name-Last: Si
Author-Name: Yutong Ding
Author-X-Name-First: Yutong
Author-X-Name-Last: Ding
Author-Name: Ershun Pan
Author-X-Name-First: Ershun
Author-X-Name-Last: Pan
Author-Name: Lifeng Xi
Author-X-Name-First: Lifeng
Author-X-Name-Last: Xi
Title: Exploratory performance evaluation and ranking for complex network systems based on the extension of GFA-DEA approach
Abstract:
In complex systems with expansive operations, the connections between inputs and outputs are complicated and multifaceted, requiring deep insights into network systems to extend to multi-stage evaluation. Meanwhile, the inherent uncertainty including data insufficiency and interrelation may hinder the applicability of conventional efficiency evaluation models. And it is crucial to figure out the appropriate inputs and outputs from a wide range of potential indicators. Therefore, this paper proposes an exploratory performance analysis and ranking model for complex systems with network structures and uncertainties based on the extension of the combination of data envelopment analysis (DEA), grey theory, and factor analysis (GFA-DEA). It can be used as a supplementary tool for exploratory analysis of complex systems as the requirements for basic data are not excessive. The illustrative application shows the extended model concludes relatively consistent results with network DEA models and provides complementary information with simplified model formulation and computational complexity. [Submitted: 4 September 2023; Accepted: 25 August 2024]
Journal: European J. of Industrial Engineering
Pages: 514-549
Issue: 4
Volume: 20
Year: 2025
Keywords: performance evaluation and ranking; network structure; exploratory analysis; complex systems.
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Handle: RePEc:ids:eujine:v:20:y:2025:i:4:p:514-549