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European Journal of Industrial Engineering

European Journal of Industrial Engineering (EJIE)

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European J. of Industrial Engineering (37 papers in press)

Regular Issues

  • The impact of online sales in centralized and decentralized dual-channel supply chains   Order a copy of this article
    by Subrata Saha 
    Abstract: This paper studies a supply chain structure featuring two different types of distribution channels through which manufacturers sell products. The centralised and decentralised distribution channels considered in this study are affected by online sales outside the structured channels. In the centralised distribution channel, two retail stores located in geographically distinct markets are operated by a single owner. In the decentralised distribution channel, two retailers independently operate two retail stores. In the non-cooperative scenario, the manufacturer always prefers the decentralised distribution channel irrespective of whether an online channel is used. To achieve channel coordination, a revenue-sharing contract is applied, but it can be used to coordinate only the decentralised distribution system. Therefore, a modified revenue-sharing contract is proposed to coordinate the centralised distribution system. The analytical study reveals that without coordination among the channel members, the manufacturer always earns maximum profit in decentralised distribution systems. However, if the supply chain is coordinated, then the manufacturer receives more benefits from using the centralised distribution systems under certain conditions. Propositions are presented to describe the characteristics of distribution structures, and to provide meaningful management guidelines for coordinating them. Extensive numerical investigations are also presented.
    Keywords: Supply chain management; Dual-channel supply chain; Revenue sharing contract; Pricing strategy; Stackelberg.
    DOI: 10.1504/EJIE.2018.10011153
  • Risk-Averse Joint Facility Location-Inventory Optimization for Green Closed-Loop Supply   Order a copy of this article
    by Guodong Yu, Pengcheng Dong, Ying Xu, Xiao Zhao 
    Abstract: This paper considers a joint facility location-inventory optimisation for green closed-loop supply chain network design under demand uncertainty. Under the uncoordinated inventory policy, we propose a chance-constrained risk-averse bi-objective 01 mixed-integer nonlinear stochastic programming to minimise the total expected cost and CO2 emissions. To solve the model, we first present an equivalent reformulation with a single objective based on distributionally robust optimisation. Then, we provide a linear reformulation with some valid inequalities. We also provide a greedy heuristic decomposition searching rule to solve the large-scale problem. We finally present a numerical analysis to show the performance of our methods. Results illustrate that the risk-averse joint model can effectively improve service capability and reliability than independent and risk-neutral location and inventory problems. We also recommend that the incompletely uncoordinated strategy for the joint optimisation can be more cost-effective and generate fewer workloads. Besides, the proposed algorithm achieves a more desirable performance than CPLEX for large-scale problems.
    Keywords: green closed-loop supply chain; facility location; inventory; risk-averse; chance constraint; distributionally robust optimisation.
    DOI: 10.1504/EJIE.2023.10046132
  • A survey on network design problems: main variants and resolution approaches   Order a copy of this article
    by Imen Mejri, Safa Bhar Layeb, Farah Zeghal 
    Abstract: Over the last decades, network design problems (NDPs) have been one of the most investigated combinatorial optimisation problems that are still catching the interest of both practitioners and researchers. In fact, NDPs pose significant algorithmic challenges, as they are notoriously NP-hard, and arise in several applications, mainly in logistics, telecommunication, and production systems. Based on the literature published mainly between 1962 and 2021, this paper provides a comprehensive taxonomy of NDPs and also identifies the most investigated variants as well as their main fields of application. This taxonomy highlights the diversity as well as the assets of this core class of operations research problems. Moreover, the main mathematical formulations and solution methods are reported. Finally, directions for future research on NDPs are derived.
    Keywords: network design problems; NDPs; literature review; survey; combinatorial optimisation.
    DOI: 10.1504/EJIE.2022.10046171
  • On designing a cumulative sum control chart using generalized Conway-Maxwell-Poisson distribution for monitoring the count data   Order a copy of this article
    by Fakhar Mustafa, Rehan Ahmad Khan Sherwani, Muhammad Ali Raza 
    Abstract: This study proposes a multipurpose cumulative-sum control chart based on the generalised Conway-Maxwell Poisson (GCOMP) distribution and names it the GCUSUM control chart. The proposed control chart monitors dispersed count data considering tail behaviour. Further, the proposed chart can also monitor zero-inflated count data. The proposed chart’s in-control and out-of-control performance analyses have been conducted using different run-length (RL) criteria. A comparative study has been presented to show the effectiveness of the proposed GCUSUM chart over established charts for monitoring distinctive features of the count data. It has been observed that the proposed control chart is efficient in monitoring the under- and over- dispersion in the count data while considering the tail behaviour. The GCUSUM chart also monitors the zero-inflated count data without utilising the zero-inflation property. Numerical and real-life examples also validate the effectiveness of the proposed control chart. [Received: 24 July 2022; accepted: 25 April 2023]
    Keywords: control chart; SPC; under-dispersion; over-dispersion; zero-inflation; tail behaviour.
    DOI: 10.1504/EJIE.2024.10057052
  • A hierarchical approach to schedule the two-machine flow shop problem with flexible periodic synchronized maintenance   Order a copy of this article
    by Nahla Chabbah Sekma, Hatem Hadda 
    Abstract: This paper tackles the makespan minimisation for the well-known two-machine flow shop problem with flexible periodic maintenance activities on both machines. The maintenance starting dates are to be decided along with the job’s sequence. We adopt a hierarchical approach in which we first decide the job's sequence and then the maintenance starting dates. We identify a dominance rule and a polynomial case, and construct an enhancement procedure. We develop and test several variants of Tabu search and simulated annealing metaheuristics. We also propose an adaptation of the well-known NEH heuristic. The experimental study shows the superiority of one of the variants of simulated annealing and the efficiency of the dominance rule. [Submitted: 15 July 2022; Accepted: 8 May 2023]
    Keywords: flow shop scheduling; flexible maintenance; Tabu search; simulated annealing.
    DOI: 10.1504/EJIE.2024.10057224
  • A Study on Pricing and Recycling Strategies for Retailers with Consideration of Selling New and Refurbished Products   Order a copy of this article
    by Yeu-Shiang Huang, Chih-Chiang Fang, Yi-Hsiang Tso 
    Abstract: Used products can be recycled for remanufacturing, but refurbished products may still compete with new products in a market since some price-sensitive consumers may be attracted by a low price. Therefore, firms should make price decisions for new and refurbished products with caution. This study investigates a retailer's pricing and recycling strategies for two types of consumers: quality-oriented consumers and price-sensitive consumers. The work examines internal and external competition between new and refurbished products with the consideration of consumer heterogeneity. A Stackelberg game theoretic model will be considered in the study, in which the manufacturer is a leader, who determines the official price and wholesale price first, and the retailer is a follower, who then accordingly develops optimal pricing strategies considering the two recycling policies. The analytical results show that retailers would rather recycle products on their own than outsource recycling if they were more capable of remanufacturing.
    Keywords: pricing; remanufacturing; consumer heterogeneity; game theory.
    DOI: 10.1504/EJIE.2024.10057620
  • Evaluating Dispatching Rules for Make-to-Availability under Simplified Drum-Buffer-Rope: a Computational Experiment   Order a copy of this article
    by Robson Flávio Castro, Roberto Fernandes Tavares Neto, Moacir Godinho Filho 
    Abstract: This research evaluates the impact of some dispatching rules (DR) on the performance of make-to-availability (MTA) under the simplified drum-buffer-rope (S-DBR) system. S-DBR/MTA seeks to ensure the availability of finished products to meet demand, so production needs to replenish inventory quickly. The DR has an important influence on the replenishment speed, which dictates the performance of such systems. We evaluate four rules found in the literature (FIFO, AT, SPT, and SRPT), two of the S-DBR/MTA (PSP and PSP1), and six rules combining the two groups (PSP-AT, PSP-SPT, PSP PSP1-AT, PSP1-SPT, and PSP1-SRPT) using a computational experiment. We use the following measures to evaluate the performance of such rules: service level, average inventory in the system, mean flow time, and stock rate per service level percentage. The PSP1-SPT rule gets better results than others, increasing the S-DBR/MTA performance.
    Keywords: make-to-availability; MTA; simplified drum-buffer-rope; S-DBR; theory of constraint; dispatching rule; DR; flow-shop.
    DOI: 10.1504/EJIE.2024.10057827
  • The Solution of Bi-Criteria Flow Shop Scheduling Problem through Mathematical Modelling and its Application in a Shoe Factory   Order a copy of this article
    by Ay?e Çelik, Serkan Kaya 
    Abstract: This paper addresses a problem occurring in a real-life shoe manufacturing factory consisting of 28 machines. Due to a large number of orders, frequent and long delays in the delivery of the products to customers occurs, which costs the factory a significant amount. The problem is formulated as a flow shop scheduling (FSS) problem and a 01 integer goal programming model is developed. Computational experiments indicate that problems with up to 50 jobs can be solved within a reasonable time by the developed model. A comparison of the results with the actual case in the factory revealed that, on the average, an improvement of 72.0% in total tardiness (TT) was achieved while an improvement of 3.9% was achieved in the maximum completion time. This helped to save the factory significantly.
    Keywords: flow shop scheduling; FSS; 0–1 integer goal programming model; shoe manufacturing; makespan; total tardiness; TT.
    DOI: 10.1504/EJIE.2024.10057892
  • Hotel Overbooking, Capacity Rationing and Cooperation with Third-Parties: A Two-Period Optimization Model   Order a copy of this article
    by Nazli Karatas Aygun, Onder Bulut 
    Abstract: We propose a two-period optimisation model for a hotel revenue management (RM) problem where overbooking, capacity rationing and cooperation with third-party websites are simultaneously considered. In a Stackelberg game structure, the hotel first sets the price, and overbooking and rationing levels, and as the followers, third-parties decide their effort levels by a Nash game. The proposed model is solved using a genetic algorithm. An extensive numerical study is performed to investigate the effects of multiple night stays, hotel effort level, and hotel capacity on the decisions and the hotel profit. It is shown that the value of capacity rationing increases with multiple night stays and the expected profit of the third-parties is decreasing with the hotel effort level but the relation between the hotel effort level and profit is not monotone. As the hotel capacity is expanded, the effort level of the third-parties and the hotel profit increase. [Submitted: 1 December 2021; Accepted: 26 May 2023]
    Keywords: pricing; overbooking; third-party websites; multiple night stays; multiple customer classes; two-period optimisation model.
    DOI: 10.1504/EJIE.2024.10058072
  • The influence of shelf life on the integrated production scheduling and vehicle routing optimization for perishable products   Order a copy of this article
    by Hercules Tadeu Asato Dantas, Roberto Fernandes Tavares Neto, Juliana K. Sagawa 
    Abstract: Prior studies on integrating production and distribution optimisation highlight the benefits of such an approach. However, no studies regarding standardised metrics for categorising shelf life lengths in different scenarios were found. Moreover, the current literature does not address the change of behaviour on solving strategies accordingly to different shelf life profiles. To address these gaps, this research proposes the normalised shelf life metric to classify long and short shelf life products. Additionally, we present a simplified optimisation formulation for the integrated production scheduling and vehicle routing problem. By evaluating three solution methods (MILP model, genetic algorithm, and logic-based Benders decomposition model), our findings reveal that shelf life significantly affects solution performance. These results emphasise the need for research focused on solution methods tailored specifically for short shelf life products. [Submitted: 26 July 2022; Accepted: 7 June 2023]
    Keywords: shelf life; production-distribution integration; perishable products; genetic algorithm.
    DOI: 10.1504/EJIE.2024.10058090
  • Robust supplier selection under uncertain costs and delivery delay times   Order a copy of this article
    by Cassiano Tavares, Pedro Munari, Moacir Godinho Filho 
    Abstract: We address the supplier selection problem under uncertainty, motivated by the current economic situation of global trade. The intense search among organisations for responsiveness in meeting market demands has directed efforts toward supply chain optimisation. Consequently, the decision regarding the best supplier choice has become vital for the success of organisations, requiring a high level of accuracy and assertiveness under complex and uncertain environments. To support decision-making in global sourcing environments, we propose a robust optimisation model that incorporates cost and time uncertainties that commonly arise in the context of worldwide raw materials supply. The model includes raw materials inventory management, preventing stockouts and violations of physical storage constraints, while considering deviations of the uncertain parameters. We analyse the behaviour of the proposed model using 324,000 scenarios generated by Monte Carlo simulations. The results show that the proposed model increases the level of robustness without significantly increasing the value of the objective function when uncertain costs and times attain their worst-case scenarios (highest deviation). On average, the objective function values increased only 3.58% in the worst case, considering 20 products, 40 periods, 60 suppliers, and an uncertainty level of 50%. [Submitted: 1 June 2022; Accepted: 10 May 2023]
    Keywords: supplier selection; uncertainty; inventory; VUCA; robust optimisation.
    DOI: 10.1504/EJIE.2024.10058218
  • Multi-objective University Rescheduling Problem by Fuzzy Programming Technique   Order a copy of this article
    by Sunil Bhoi, Jayesh Dhodiya 
    Abstract: This study presents multi-objective university rescheduling assignment problem (MOURAP), when some faculty members have been left the institute due to unavoidable circumstances, i.e., disruptions. This presented model executed in two phases. The first phase discuss and formulate the university course rescheduling problem and allocate all unassigned courses to available faculty members based on preferences for course of faculty members, administrator and indirect students preferences computed on faculty feedback and student result analysis. In second phase, pair of faculty member and course assigned to time slots based on faculty member preferences. The prime aim of rescheduling is to minimise the course allocation change from former and latter to faculty members and time slots allocations change from initial and new schedule to faculty members and students. To test the strength of presented model, this study demonstrated the model with two numerical examples on hypothetical data. With hypothetical numerical data, model has been executed and generated new schedule by fuzzy programming technique wit linear and exponential membership functions. This technique always produced non-dominated/compromise solutions. Results are obtained using LINGO19.0 software. [Submitted: 14 January 2022; Accepted: 9 July 2023]
    Keywords: university scheduling; rescheduling; 0-1 integer programming; fuzzy programming technique.
    DOI: 10.1504/EJIE.2024.10058383
  • Compact MILP Models for Double Row Layout Problem with Pairwise Clearance   Order a copy of this article
    by Richard Alaimo, Churlzu Lim 
    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. [Submitted: 9 February 2022; Accepted: 11 August 2023]
    Keywords: facility layout; double row layout problem; mixed-integer linear programming; combinatorial optimisation; clearance requirements.
    DOI: 10.1504/EJIE.2025.10060235
  • Pragmatic simultaneous scheduling of machines, AGVs, tool transporter and tools in a multi machine FMS using flower pollination algorithm   Order a copy of this article
    by Sivarami Reddy N, V.Ramamurthy Dwivedula, Prahlada Rao K, Padma Lalitha M 
    Abstract: This paper deals with machines, automated guided vehicles (AGVs), tool transporter (TT) and tools simultaneous scheduling in multi-machine flexible manufacturing system considering parts and tools transfer times for makespan minimisation. Only one copy of every tool type is made available due to economic restrictions and the tools are stored in central tool magazine that shares with and serves for several machines. TT and AGVs carry tools and jobs between machines. This simultaneous scheduling problem is highly complex in nature as it involves allocating tools, AGVs and associated trip operations including the dead heading and loaded trip times of both AGVs and TT to job-operations, job operations sequencing on machines. This paper presents nonlinear mixed integer programming formulation to model this problem and flower pollination algorithm (FPA) is employed to solve it. The results have been tabulated, analysed and compared. An industrial problem in manufacturing company is used for verification. [Received 18 October 2020; Accepted 26 May 2023]
    Keywords: flexible manufacturing systems; automated guided vehicles; AGVs; scheduling of jobs; TT and tools; optimisation techniques; flower pollination algorithm; FPA; makespan.
    DOI: 10.1504/EJIE.2024.10059497
  • Performance Analysis for A Dual-Crane Automated Storage and Retrieval System   Order a copy of this article
    by Letitia M. Pohl, Mahmut Tutam 
    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. [Submitted: 12 September 2022; Accepted 17 July 2023]
    Keywords: unit-load warehouse; automated storage and retrieval systems; AS/RS; dual-crane; optimal buffer position; throughput models.
    DOI: 10.1504/EJIE.2025.10059498
  • A multi-period inventory model with price, time and service level dependent demand under preservation technology investment   Order a copy of this article
    by Sudarshan Bardhan, Indrani Modak, Bibhas Chandra Giri 
    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. [Submitted: 23 December 2022; Accepted: 3 August 2023]
    Keywords: price dependent demand; learning effect; preservation technology; service level; multi-period inventory model.
    DOI: 10.1504/EJIE.2025.10059500
  • Optimum Design of an Efficient Variables Sampling System for Validating Process Yield with Six-Sigma Quality Requirement and Creation of a Cloud-Computing Tool   Order a copy of this article
    by Chien-Wei Wu, Ming-Hung Shu, Bi-Min Hsu, To-Cheng Wang 
    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]
    Keywords: Six Sigma; process yield; lot sentencing; alterable acceptance standard ; tightened-normal-tightened sampling system.
    DOI: 10.1504/EJIE.2025.10059660
  • Sensitivity comparison of control charts under MAD shift detector using the rank set sampling scheme   Order a copy of this article
    by Nadia Saeed, A. Bushawiesh 
    Abstract: In this article, the sensitivity comparison of the standard Shewhart S-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 (ARL1), 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. [Submitted: 26 November 2022; Accepted: 11 August 2023]
    Keywords: rank set sampling; RSS; control chart; shift detector; outliers; median absolute deviation; MAD; percentile points; average run length; ARL.
    DOI: 10.1504/EJIE.2025.10060058
  • An EPQ model with different demand and deterioration rate for two warehouses under shortage, learning and imperfect production.   Order a copy of this article
    by S. V. Singh Padiyar, Vandana Gupta, S.R. Singh, Naveen Bhagat 
    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. [Submitted: 28 January 2022; Accepted: 23 August 2023]
    Keywords: two warehouses; imperfect production; shortage; deterioration; learning effect.
    DOI: 10.1504/EJIE.2025.10060653
  • A hybrid approach of genetic algorithm and truncated branch-and-bound for seru scheduling problem with sequence-dependent setup time   Order a copy of this article
    by Xiaohong Zhang, Zhe Zhang, Xiaoling Song, Xiaofang Zhong 
    Abstract: This paper concentrates on the seru scheduling problem considering sequence-dependent setup time to minimise the makespan, in which seru 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. [Submitted: 31 October 2022; Accepted: 25 September 2023]
    Keywords: seru production system; setup times; scheduling; genetic algorithm; branch-and-bound.
    DOI: 10.1504/EJIE.2025.10060760
  • Applying a Modified Adaptive Large Neighborhood Search for Truck Scheduling and Pile Assignment in a Two-Stage Sorting System   Order a copy of this article
    by James C. Chen, Tzu-Li Chen, Yin-Yann Chen, Yung-Hsin Su 
    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. [Submitted: 30 January 2023; Accepted: 25 August 2023]
    Keywords: truck scheduling; two-stage sorting system; modified adaptive large neighbourhood search.
    DOI: 10.1504/EJIE.2025.10061219
  • Pricing and Greening Strategies in a Dual-channel Supply Chain with Government tariffs and Cannibalisation under Demand Uncertainty   Order a copy of this article
    by Amit Ranjan, Anand Ranjan, J.K. Jha 
    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. [Submitted: 20 April 2023; Accepted: 9 October 2023]
    Keywords: dual-channel supply chain; government tariffs; cannibalisation; uniform distribution; distribution-free.
    DOI: 10.1504/EJIE.2025.10061256
  • Improving the Quality of Production through the Six Sigma Method in a Textile Business   Order a copy of this article
    by İzzettin Hakan Karaçizmeli 
    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%. [Submitted: 23 May 2023; Accepted: 16 October 2023]
    Keywords: quality; textile; Six Sigma; process improvement; seam mark.
    DOI: 10.1504/EJIE.2025.10061430
  • Shift scheduling and rostering with same shift-type and weekend-off fairness constraints in call centres   Order a copy of this article
    by Ruicheng Wang, Yue Xu, Xiuli Wang 
    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. [Submitted: 21 March 2023; Accepted: 12 November 2023]
    Keywords: call centre; shift scheduling; rostering; integer programming; optimal algorithm; heuristic algorithm; neighbourhood search; weekend-off fairness; same shift-type; operations management.
    DOI: 10.1504/EJIE.2025.10061821
  • A Multi-Objectives Optimization Model for the Joint Design of Statistical Process Control and Engineering Process Control   Order a copy of this article
    by Salih Osman Duffuaa, Omar Dehwah, Abdul-Wahid Al-Saif, Anas Alghazi, Awsan Mohammed 
    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 can 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. [Submitted: 31 July 2023; Accepted: 26 November 2023]
    Keywords: statistical process control; SPC; engineering process control; EPC; multi-objectives; control charts; process monitoring.
    DOI: 10.1504/EJIE.2025.10061955
  • An Agile Optimization Algorithm for the Multi-Source Team Orienteering Problem   Order a copy of this article
    by Mattia Neroni, Javier Panadero Martinez, Elnaz Ghorbani, Majsa Ammouriova, Angel A. Juan 
    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 NP-hard, 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]
    Keywords: agile optimisation; biased-randomised heuristics; team orienteering problem; TOP; dynamic scenarios.
    DOI: 10.1504/EJIE.2025.10062276
  • Research on Pricing Strategy of Closed-loop Supply Chain Based on PIR and Recovery Effort   Order a copy of this article
    by Jun Yao, Dongyan Chen, Hui Yu 
    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. [Submitted: 14 December 2022; Accepted: 7 November 2023]
    Keywords: process innovation for remanufacturing (PIR); recovery efforts; closed-loop supply chain; Stackelberg game; pricing strategy.
    DOI: 10.1504/EJIE.2025.10062351
  • Penalty and threshold optimisation of the retailer - vendor return contracts for contract re-negotiation in retail reverse supply chains   Order a copy of this article
    by Mehmet Erdem Coskun, Elkafi Hassini 
    Abstract: In this paper, we consider a decentralised reverse supply chain constituting of multiple vendors and an independent retailer. The vendors offer the retailer return contracts with a multi-layered penalty structure deal. We focus on the strategic decision of developing optimal vendor re-negotiation contract parameters for the retailer. We model the problem as a mixed integer nonlinear program (MINLP) where the retailer decides on the vendor penalty fees and return thresholds simultaneously. We propose an efficient solution approach based on decomposing by decoupling the decision on penalty fees and return thresholds. The resulting problems are linear and we used them to provide rules for re-negotiation tactics for the retailer. We find that the retailer can save up to 7% from re-negotiation their contract terms. [Received: 16 June 2022; Accepted: 26 February 2023]
    Keywords: retail; reverse supply chain; decentralised decision making; coordination; vendor contracts; buyback contracts; return contracts; contract terms; product returns; retail returns; returns management; multi-layered penalty structure; piece-wise linear; optimisation; rule-of-thumb.
    DOI: 10.1504/EJIE.2024.10055607
  • Reliable global supply chain network design under supply disruptions   Order a copy of this article
    by Changjun Wang, Mao Mao 
    Abstract: This paper studies a reliable global supply chain (GSC) design subject to uncertain supply disruptions with underlying correlation. A two-stage distributionally robust model is developed, where the joint disruption distributions are captured by an ambiguous set under a set of known marginal disruption probabilities. The proactive strategies and recourse decisions are optimised in an integrated way, the former considering the selection of suppliers, plants, and product design solutions, while the latter including multi-source procurement. We uncover the relationship between the closed-form worst-case joint distribution and the marginal disruption probabilities by proving the supermodularity of the recourse model. Therefore, the proposed min-max-min model can be equivalently reformulated as a stochastic program. Finally, an experimental study is performed. Our approach not only saves lots of costly efforts in enhancing the visibility of GSC disruptions, but also provides a promising alternative for addressing GSC design in a complex and uncertain setting. [Received: 16 August 2022; Accepted: 3 March 2023]
    Keywords: global supply chain network; supply disruption; reliability; two-stage distributionally robust; supermodularity.
    DOI: 10.1504/EJIE.2024.10055919
  • A GVNS-based approach for periodic consumables delivery to home hemodialysis patients: a case study   Order a copy of this article
    by Haifa Nouira, Adnen El-Amraoui, Sondes Hammami, Gilles Goncalves, Hanen Bouchriha 
    Abstract: The use of home hemodialysis (HHD) has the potential to lower healthcare costs while improving quality-adjusted survival and quality of patient's life. Nevertheless, the number of patients on this modality of dialysis remains low due to several barriers among which the problem of storage capacity. In fact, patients have a limited storage capacity in their homes, so they cannot store the required consumables (i.e., commodities) for long-term treatment sessions. Therefore, to promote HD use by dialysis patients, healthcare systems should offer flexible service that satisfies the patient's need in term of delivery frequency. Getting inspired by the periodic vehicle routing problem (PVRP), we develop here a mathematical formulation of the considered problem, and we propose a new approach based on the general variable neighbourhood search metaheuristic (GVNS) to solve it, due to its NP-hardness. To illustrate the effectiveness of the proposed approach, several tests have been performed. [Received: 9 August 2022; Accepted: 23 March 2023]
    Keywords: home dialysis care; periodic VRP; GVNS metaheuristic; visit frequency choice; cluster-first route-second heuristic approach.
    DOI: 10.1504/EJIE.2024.10057561
  • A multiple agent-based system for the intelligent demand planning of new products   Order a copy of this article
    by Hokey Min, Wen-Bin Yu 
    Abstract: New product development (NPD) is pivotal in the firm's innovation and organic growth. Despite its strategic importance to the firm's success, it poses many managerial challenges for the effective launch of new products due to the inherent difficulty in new product demand planning. Such difficulty stems from an absence of historical sales data, shortened product life cycles, and a rapid shift in today's consumer behaviours. To deal with those demand planning challenges, this paper aims to propose a multiple agent-based system (ABS) that can overcome the shortcomings of traditional demand forecasting tools and improve forecasting accuracy significantly through the inclusion of meaningful information available from both internal and external data sources. The proposed ABS incorporates causal information obtained from four different types of agents: the coordination agent, the task agent, the data collection agent, and the interface agent. Through a series of simulation experiments, we found that the ABS improved forecasting accuracy over the traditional forecasting methods in demand planning situations where only a limited amount of historical data is available in the early introductory stages of NPD. [Received: 11 August 2022; Accepted: 24 March 2023]
    Keywords: new product development; NPD; demand planning; agent-based system; ABS; simulation; business intelligence; predictive analytics.
    DOI: 10.1504/EJIE.2024.10056239
  • A bi-objective MILP model for an open-shop scheduling problem with reverse flows and sequence-dependent setup times   Order a copy of this article
    by Saba Aghighi, Esmaeil Mehdizadeh, Seyed Taghi Akhavan Niaki, Amir Abbas Najafi 
    Abstract: In this research, the scheduling problem of open-shop scheduling problem (OSSP) with sequence-dependent setup time (SDST) is investigated considering the reverse flow (assemble/disassemble flow on the same machines). The problem is formulated as a bi-objective mixed-integer linear programming (MILP) model. It involves reverse flows to minimise the completion time (Cmax) and total tardiness. Since the OSSP is an NP-hard problem, a vibration damping-based multi-objective optimisation algorithm (MOVDO) is employed to solve large test problems in a reasonable runtime. Analysing the results of this algorithm was compared to an Epsilon-constrained method, which produced similar results in small problem sizes. Additionally, this algorithm is compared to other multi-objective algorithms, such as MOACO, MO-Cuckoo search, and NSGA-II, in terms of its performance. Based on the performance of these algorithms, we show that the proposed MOVDO algorithm performs better than the other algorithms to solve this problem. Eventually, a case study is investigated to validate the mathematical model and demonstrate the application. Comparing the proposed model to the results in the real world, the proposed model shows an improvement. [Received: 3 August 2021; Accepted: 2 April 2023]
    Keywords: open-shop scheduling problem; OSSP; reverse flows; sequence-dependent setup times; SDST; vibration damping-based optimisation algorithm; MOVDO.
    DOI: 10.1504/EJIE.2024.10059187
  • An exact solution method for seru scheduling problems with multiple rate-modifying activities and learning effect   Order a copy of this article
    by Yujing Jiang, Zhe Zhang, Xue Gong, Yong Yin 
    Abstract: This study investigates two seru scheduling problems in a seru production system (SPS) with multiple rate-modifying activities and DeJong's learning effect to minimise the total completion time and the total waiting time. Upon reformulating two seru scheduling problems to assignment problems, the calculation time is confirmed; these two seru scheduling problems can be solved in polynomial time if the job allocation vector is given in advance. Then, a general exact solution method is proposed to obtain the optimal schedule. Computational experiments and sensitivity analysis on learning effect are also designed to test the performance of proposed exact solution method. The results indicate that the frequency of rate-modifying activity is not the more the better, nor the less the better in improving the production efficiency, a balance between modifying rate and modifying times should also be considered in practical SPS production. The proposed exact solution method can provide the optimal solution in reasonably implementing rate-modifying activity strategies and scheduling jobs to reach the shortest total completion time or job waiting time. This study will instructively help SPS shorten production cycle, improve productivity and order responsiveness to some extent. [Received: 28 December 2021; Accepted: 28 December 2022]
    Keywords: seru scheduling; rotating seru; exact solution method; assignment problem; rate-modifying; learning effect.
    DOI: 10.1504/EJIE.2024.10060933
  • Solving the stochastic machine assignment problem with a probability-based objective: problem formulation, solution method and practical applications   Order a copy of this article
    by Kuo-Hao Chang, Robert Cuckler 
    Abstract: In this research, a variation of the assignment problem is formulated. Diverging from many studies which model the assignment problem in a deterministic setting, we consider a noisy and complex manufacturing process consisting of several workstations, each of which must be assigned a machine from a set of machine types which vary randomly according to processing time. The objective is to determine the optimal assignment solution which maximises the probability that a production task is completed within a prespecified completion time interval. To solve the proposed problem, we develop an efficient simulation optimisation method which incorporates a factor screening method into a nested partitions-based framework. A series of numerical experiments are conducted to test the efficiency of the proposed algorithm in comparison to competing ones. Compared to existing algorithms, the proposed solution methodology was able to find feasible machine assignment solutions which generated substantially higher probabilities of job completion. [Received: 29 September 2022; Accepted: 16 February 2023]
    Keywords: production management; production planning; simulation applications; simulation optimisation.
    DOI: 10.1504/EJIE.2024.10057324
  • Developing a hybrid genetic algorithm in a vehicle routing problem with simultaneous delivery and pickup with time windows: optimising fuel consumption   Order a copy of this article
    by Nilufa Yeasmin, Sultana Parveen, Anjuman Ara 
    Abstract: The environmental deterioration due to fossil fuel burning is the significant issue in logistic industry. This issue motivates the transportation industry to improve distribution activities. The vehicle routing problem (VRP) is concerned with developing eco-distribution activities in the logistics industry. Therefore, this study considers the VRP with simultaneous delivery and pickup with time windows (VRPSDPTW), a variant of VRP and develops an environmental fuel optimisation model for VRPSDPTW to optimise the vehicle fuel consumption. This study proposes a hybrid genetic algorithm (HGA) to solve the developed fuel optimisation model and applies GA to examine the operational efficiency of HGA. Finally, this study executes the computational experiment of two algorithms to solve the developed model under two alternate issues, i.e., fuel-oriented and distance-oriented. We found that the developed model under the fuel-oriented module reduces better fuel consumption, and the HGA performs better than GA regarding fuel consumption. [Received: 29 August 2022; accepted: 16 February 2023]
    Keywords: fuel optimisation; VRPSDPTW; genetic algorithm; hybrid-genetic algorithm.
    DOI: 10.1504/EJIE.2024.10057051
  • Designing the agile green sustainable multi-channel closed-loop supply chain with dependent demand to price and greenness under epistemic uncertainty   Order a copy of this article
    by Elham Kouchaki Tajani, Armin Ghane Kanafi, Maryam Daneshmand-Mehr, Ali-Asghar Hosseinzadeh 
    Abstract: The increasing pressure and intensity of world competition in business environments, which is ever-changing, has doubled the necessity of proper reactions by industrial manufacturing organisations and companies. Therefore, this paper proposes a novel design of a closed-loop supply chain with multiple forms of product distribution and collection that aim to maximise profit and social responsibility while minimising delays in delivery and environmental pollution. The proposed model uses two indices, local employment and the number of jobs created, to show the performance of the function of social responsibility. Further, by mentioning pricing and greenness levels for the products in the paper, we formulate customer demands dependent on the price and greenness of the products. Also, RFID technology is considered for every vehicle to reduce time lags during transportation. Besides, the modelling is performed according to a possibilistic mean-absolute deviation approach due to the uncertain nature of some parameters. Eventually, the augmented ε-constraint method is utilised to solve and its validation. The results revealed that the proposed model could provide efficient decisions that can be a suitable tool for managers and experts, and it can have extensive application, particularly from a strategic perspective. [Received: 9 October 2022; Accepted: 6 April 2023]
    Keywords: multi-channel; pricing; RFID; possibilistic programming.
    DOI: 10.1504/EJIE.2024.10059496
  • An adaptive large neighbourhood search for multi-depot electric vehicle routing problem with time windows   Order a copy of this article
    by Yucong Wang, Ping Chen 
    Abstract: The multi-depot electric vehicle routing problem with time windows (MDEVRPTW) is an extension of the electric vehicle routing problem with time windows (EVRPTW). Due to the driving range limit, the EVs need to recharge at some charging stations en route. In the MDEVRPTW, the EVs depart from different depots, visit the assigned customers for delivery, and finally return to the depot where they leave. The EVs could recharge at any depot or public charging station whenever necessary. This problem is formulated as a mixed-integer linear programming model, and an adaptive large neighbourhood search algorithm is proposed for solving it. In the proposed approach, both general and problem-specific destroy and repair operators are applied to improve solution quality. Numerical results show that the proposed approach can obtain high-quality solutions within less computing time and an elite version of the proposed ALNS could perform better than the complete version. [Received: 20 August 2021; Accepted: 25 April 2023]
    Keywords: electric vehicle routing problem; multi-depot; time windows; charging station; adaptive large neighbourhood search.
    DOI: 10.1504/EJIE.2024.10057555