Template-Type: ReDIF-Article 1.0
Author-Name: Mohammadtaghi Falsafi
Author-X-Name-First: Mohammadtaghi
Author-X-Name-Last: Falsafi
Author-Name: Davide Masera
Author-X-Name-First: Davide
Author-X-Name-Last: Masera
Author-Name: Julien Mascolo
Author-X-Name-First: Julien
Author-X-Name-Last: Mascolo
Author-Name: Rosanna Fornasiero
Author-X-Name-First: Rosanna
Author-X-Name-Last: Fornasiero
Title: A decision-support model for dock and transport management after inbound logistics disruptions in the automotive sector
Abstract:
One of the major disruptions in automotive supply chain is related to the on-time arrival of components from suppliers to assembly plants. In this paper, we develop an operative decision-support model to avoid the ripple effect of these disruptions on production scheduling. In particular, based on strategies for truck-dock re-assignment and transport mode selection, the model is applied to a case study at Fiat Chrysler Automobiles (FCA). Moreover, the paper elaborates on the resilience and robustness of the supply chain in dealing with vulnerabilities in different phases of decision-making. The model allows supply chain managers to efficiently organise the transport modes of delayed orders, the in-plant material handling equipment, the arrival of trucks in the parking lot, and the use of inbound docks. [Submitted: 10 January 2021; Accepted: 5 April 2021]
Journal: European J. of Industrial Engineering
Pages: 268-293
Issue: 3
Volume: 16
Year: 2022
Keywords: disruption management; automotive sector; inbound logistics; dock management; transport management; supply chain resilience; truck-dock rescheduling; mixed-integer linear programming; MILP.
File-URL: http://www.inderscience.com/link.php?id=121895
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Handle: RePEc:ids:eujine:v:16:y:2022:i:3:p:268-293
Template-Type: ReDIF-Article 1.0
Author-Name: Tarit Rattanamanee
Author-X-Name-First: Tarit
Author-X-Name-Last: Rattanamanee
Author-Name: Suebsak Nanthavanij
Author-X-Name-First: Suebsak
Author-X-Name-Last: Nanthavanij
Title: Heuristic procedure for bi-capacitated multiple-trip vehicle routing problem
Abstract:
The multiple-trip vehicle routing problem with physical workload (MTVRP-WL) or bi-capacitated MTVRP is intended to find an optimal number of delivery trucks and their travel routes to serve a set of customers having constant load demands within a given time limit. Delivery workers who are pre-assigned to trucks must manually unload goods at customer locations. Both trucks and workers are heterogeneous in terms of the load capacity and working energy capacity, respectively. Initially, the random nearest neighbourhood search technique is employed to generate an initial feasible solution. Then, the solution is improved using two local search operators, namely, greedy swap and 2-opt. The improvement algorithms are repeated for a number of iterations until no further improvement is obtained. From a computation experiment, the heuristic procedure is found to be efficient since it can obtain near-optimal MTVRP solutions in reasonable computation time. [Submitted: 5 November 2020; Accepted: 7 April 2021]
Journal: European J. of Industrial Engineering
Pages: 294-316
Issue: 3
Volume: 16
Year: 2022
Keywords: multiple-trip vehicle routing problem; bi-capacitated problem; heuristic algorithm; local search; physical workload; intra-city logistics.
File-URL: http://www.inderscience.com/link.php?id=121904
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Handle: RePEc:ids:eujine:v:16:y:2022:i:3:p:294-316
Template-Type: ReDIF-Article 1.0
Author-Name: Chengfeng Wu
Author-X-Name-First: Chengfeng
Author-X-Name-Last: Wu
Author-Name: Qiuhong Zhao
Author-X-Name-First: Qiuhong
Author-X-Name-Last: Zhao
Author-Name: Chunfeng Xu
Author-X-Name-First: Chunfeng
Author-X-Name-Last: Xu
Title: Supply chain optimal ordering policy under two-level trade credit with default risk
Abstract:
The paper assumes that the manufacturer offers the wholesaler trade credit, and the wholesaler provides the retailer with trade credit in a three-echelon supply chain. First, we formulate the mathematical models that include the time value of capital and the partial default risk for the three members, respectively. Second, we derive the existence and uniqueness conditions of the optimal lot-size or production quantity for the members under decentralised replenishment policy. Finally, we present the sensitivity analysis of the optimal solution with respect to the parameters to provide managerial insights. The results show that the larger standard deviation of the demand, the more effective trade credit as the settlement method. The key contribution of the paper is that we present an ordering model that optimises lot sizes with two-level trade credit and investigate the transmission effect of default credit risk in a three-echelon supply chain under an uncertain market environment. [Submitted: 23 September 2020; Accepted: 8 April 2021]
Journal: European J. of Industrial Engineering
Pages: 317-348
Issue: 3
Volume: 16
Year: 2022
Keywords: supply chain; two-level trade credit; default risk; newsvendor model.
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Handle: RePEc:ids:eujine:v:16:y:2022:i:3:p:317-348
Template-Type: ReDIF-Article 1.0
Author-Name: Ye-Jia Ping
Author-X-Name-First: Ye-Jia
Author-X-Name-Last: Ping
Author-Name: Ran Liu
Author-X-Name-First: Ran
Author-X-Name-Last: Liu
Author-Name: Ze-Ling Wang
Author-X-Name-First: Ze-Ling
Author-X-Name-Last: Wang
Author-Name: Hu-Chen Liu
Author-X-Name-First: Hu-Chen
Author-X-Name-Last: Liu
Title: New approach for quality function deployment with an extended alternative queuing method under linguistic Pythagorean fuzzy environment
Abstract:
As a customer-driven tool to support the development of new products or services, quality function deployment (QFD) is able to transform customer requirements (CRs) into suitable engineering characteristics (ECs) to maximise the customer satisfaction. However, the conventional QFD method has some weaknesses limiting its effectiveness in the real applications. In this study, a new QFD approach based on linguistic Pythagorean fuzzy sets (LPFSs) and alternative queuing method (AQM) is constructed to enhance the performance of the traditional QFD. First, we express the assessments from experts on the relationships between CRs and ECs using the LPFSs. Second, we apply an extended AQM to determine the importance prioritisation of ECs. Additionally, a consensus reaching algorithm is adopted to dynamically determine the relative weights of experts considering their inconsistent judgements. An illustrative application of 5G smartphone development is conducted to demonstrate the feasibility and efciency of our proposed QFD approach. Through the empirical case with a comparative analysis, the proposed approach is proved to be useful and practical for capturing experts' opinions and prioritising ECs in QFD. [Submitted: 19 March 2020; Accepted: 11 April 2021]
Journal: European J. of Industrial Engineering
Pages: 349-370
Issue: 3
Volume: 16
Year: 2022
Keywords: quality function deployment; QFD; linguistic Pythagorean fuzzy set; LPFS; alternative queuing method; AQM; consensus reaching method; product development.
File-URL: http://www.inderscience.com/link.php?id=121912
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Handle: RePEc:ids:eujine:v:16:y:2022:i:3:p:349-370
Template-Type: ReDIF-Article 1.0
Author-Name: Rylan H. Caldeira
Author-X-Name-First: Rylan H.
Author-X-Name-Last: Caldeira
Author-Name: A. Gnanavelbabu
Author-X-Name-First: A.
Author-X-Name-Last: Gnanavelbabu
Title: An improved backtracking search algorithm for the flexible job shop rescheduling problem with new job insertions
Abstract:
In real-world environments, production schedules are subject to several disruptions. Hence it is essential to account for these disruptions while constructing the production schedules. This work considers the flexible job-shop rescheduling problem (FJSRP) considering new job insertions. An improved discrete backtracking search algorithm and a slack-based inserting rescheduling strategy are proposed to address this problem considering makespan as objective. A set of heuristics is used to generate a diverse initial population. An order-preserving crossover and a mutation operator is developed to balance the exploitation and exploration. A transfer criterion is utilised to employ the information of the past population. The algorithm's exploitation capability is enhanced by employing a local search technique. Extensive computational work is performed on well-known benchmark instances. Computational results demonstrate the superiority of the proposed approach as well as the rescheduling strategy. [Received: 7 July 2020; Accepted: 27 January 2021]
Journal: European J. of Industrial Engineering
Pages: 41-70
Issue: 1
Volume: 16
Year: 2022
Keywords: backtracking search algorithm; flexible job shop rescheduling problem; job insertion; local search technique; rescheduling strategy.
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Handle: RePEc:ids:eujine:v:16:y:2022:i:1:p:41-70
Template-Type: ReDIF-Article 1.0
Author-Name: Elhassania Messaoud
Author-X-Name-First: Elhassania
Author-X-Name-Last: Messaoud
Title: Solving a stochastic programming with recourse model for the stochastic electric capacitated vehicle routing problem using a hybrid genetic algorithm
Abstract:
This study considers stochastic travel times in an electric capacited vehicle routing problem (ECVRP), where the used electric vehicles may need to visit charging stations due to their battery capacities. The main goal of the present paper is to solve a two-stage stochastic programming with recourse (SPR) model for this problem using a hybrid genetic algorithm (HGA) and a Monte Carlo sampling (MCS) procedure. To show the effectiveness of the proposed approach, the computational experiments are applied to 29 instances with up to 100 customers derived from benchmarks presented in the literature. Firstly the numerical results are compared to those found by CPLEX solver for the deterministic model, thereafter a very large number of scenarios is taken into consideration to evaluate this approach in the stochastic environment using a known probability distribution. [Received: 26 September 2020; Accepted: 5 February 2021]
Journal: European J. of Industrial Engineering
Pages: 71-90
Issue: 1
Volume: 16
Year: 2022
Keywords: transport problem; electric vehicles; capacity constraint; stochastic travel times; stochastic programming with recourse model; genetic algorithm.
File-URL: http://www.inderscience.com/link.php?id=119367
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Handle: RePEc:ids:eujine:v:16:y:2022:i:1:p:71-90
Template-Type: ReDIF-Article 1.0
Author-Name: Adolfo Rene Santa Cruz Rodriguez
Author-X-Name-First: Adolfo Rene Santa Cruz
Author-X-Name-Last: Rodriguez
Author-Name: Paulo Vitor De Oliveira
Author-X-Name-First: Paulo Vitor De
Author-X-Name-Last: Oliveira
Title: An extension of systematic layout planning by using fuzzy AHP and fuzzy VIKOR methods: a case study
Abstract:
Facility layout problem (FLP) is a complex task generally affected by multiple conflicting criteria, uncertainties, ambiguity, non-commensurable, inaccurate or incomplete information. This paper addresses these characteristics by extending the systematic layout planning (SLP) procedure with integration of SLP, fuzzy analytic hierarchy process (FAHP) and fuzzy VIKOR (FVIKOR) methods into a fuzzy multi criteria group decision making analysis. The problem is addressed in three stages: 1) feasible layout alternatives are generated using the SLP procedure; 2) the weights of the criteria are determined using FAHP; 3) FVIKOR is used to select the most appropriate layout using qualitative and quantitative criteria. We take advantage of the main characteristic of the FVIKOR method to provide a compromising solution including non-commensurable and conflicting criteria. A real-world case study on improving the layout of a production line in a suction valve industry is conducted to illustrate these approaches. The results showed the applicability and effectiveness of the SLP extension to handle FLP under fuzzy environments. [Submitted 6 January 2020; Accepted 12 January 2021]
Journal: European J. of Industrial Engineering
Pages: 1-30
Issue: 1
Volume: 16
Year: 2022
Keywords: facility layout problem; FLP; fuzzy AHP; FAHP; fuzzy VIKOR; FVIKOR; systematic layout planning; SLP.
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Handle: RePEc:ids:eujine:v:16:y:2022:i:1:p:1-30
Template-Type: ReDIF-Article 1.0
Author-Name: Yu-Hsiu Hung
Author-X-Name-First: Yu-Hsiu
Author-X-Name-Last: Hung
Author-Name: Kuan-Cheng Huang
Author-X-Name-First: Kuan-Cheng
Author-X-Name-Last: Huang
Author-Name: Taho Yang
Author-X-Name-First: Taho
Author-X-Name-Last: Yang
Title: A simulation study on CONWIP system design for bicycle chain manufacturing
Abstract:
The aim of the study was to demonstrate the effectiveness of constant work-in-process (CONWIP) pull system to bike chain production. Two multi-CONWIP production systems (developed by Kaizen, as well as by looking at the bottlenecks) were proposed to prevent WIP accumulations. Simulation was performed on the average lead time and the total WIP of the two multi-CONWIP systems in comparison with those of a current bike chain production system. Results of the comparisons showed that the Kaizen multi-CONWIP system outperformed all the other systems on the average lead time (with up to 42.8% improvements). The bottleneck multi-CONWIP system were able to reduce the WIP volume by over 50%, outperforming the Kaizen multi-CONWIP system and the current production system. These results show that multi-CONWIP has potential in reducing production lead time and WIP and can better satisfy customer demands. [Received: 18 March 2020; Accepted: 27 January 2021]
Journal: European J. of Industrial Engineering
Pages: 31-40
Issue: 1
Volume: 16
Year: 2022
Keywords: bike chain; constant work in process; CONWIP; kanban; pull production; simulation optimisation.
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Handle: RePEc:ids:eujine:v:16:y:2022:i:1:p:31-40
Template-Type: ReDIF-Article 1.0
Author-Name: Lili Wang
Author-X-Name-First: Lili
Author-X-Name-Last: Wang
Author-Name: Zhe Zhang
Author-X-Name-First: Zhe
Author-X-Name-Last: Zhang
Author-Name: Yong Yin
Author-X-Name-First: Yong
Author-X-Name-Last: Yin
Title: Order acceptance and scheduling problem with outsourcing in seru production system considering lot-spitting
Abstract:
This paper focuses on the order acceptance and scheduling problem considering lot-spitting with outsourcing decisions simultaneously in <i>seru</i> production system. Assume that the company's production capacity is limited, and that the outsourcer will require different outsourcing costs for different orders. Therefore, when the outsourcing cost of an order is relatively high, the company can choose to process it internally or reject the order directly, so that the company can achieve higher revenue. To solve this complex problem, a mixed 0-1 integer programming model is established, and the objective function maximisation of the net revenue is considered. Due to the complexity of the problem and model, an efficient hybrid algorithm named adaptive simulated annealing genetic algorithm (ASAGA) is designed for the proposed model. Finally, the experimental results show that the ASAGA has better optimal results and excellent scalability. [Received: 27 August 2019; Accepted: 6 February 2021]
Journal: European J. of Industrial Engineering
Pages: 91-116
Issue: 1
Volume: 16
Year: 2022
Keywords: order acceptance and scheduling; OAS; seru; outsourcing; lot-spitting; hybrid intelligent algorithm.
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Handle: RePEc:ids:eujine:v:16:y:2022:i:1:p:91-116
Template-Type: ReDIF-Article 1.0
Author-Name: Zhen Zhang
Author-X-Name-First: Zhen
Author-X-Name-Last: Zhang
Author-Name: Song-Tao Zhang
Author-X-Name-First: Song-Tao
Author-X-Name-Last: Zhang
Author-Name: Ming-Shi Yue
Author-X-Name-First: Ming-Shi
Author-X-Name-Last: Yue
Title: Joint ordering policy for a conditional trade credit model with two retailers
Abstract:
This paper focuses on the cooperation mechanism between two retailers. To reduce the average processing cost, the supplier usually sets a threshold for trade credit to stimulate retailers' orders. Retailers can enjoy permissible delay in payments only when their order quantities are more than or equal to the given threshold. However, considering the diversity of retailers, the motivation effect of the threshold is limited. To resolve the problem, the supplier can additionally provide its retailers with a joint-ordering policy under which they can make delayed payments as long as their total order quantity meets the required threshold. We provide a mutually acceptable order-allocation scheme for two retailers, and determine the optimal payment methods for them. In addition, an optimal threshold is identified for the supplier to maximise the total order quantity of retailers. Based on this, some managerial insights are obtained. [Submitted: 27 February 2020; Accepted: 8 April 2021]
Journal: European J. of Industrial Engineering
Pages: 398-417
Issue: 4
Volume: 16
Year: 2022
Keywords: inventory; economic order quantity; EOQ; supply chain management; conditional trade credit; joint-ordering policy; cooperation mechanism; non-cooperative game; tacit bargaining; recommended retail price; mathematical analytic tools and techniques.
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Handle: RePEc:ids:eujine:v:16:y:2022:i:4:p:398-417
Template-Type: ReDIF-Article 1.0
Author-Name: S. Ganesan
Author-X-Name-First: S.
Author-X-Name-Last: Ganesan
Author-Name: R. Uthayakumar
Author-X-Name-First: R.
Author-X-Name-Last: Uthayakumar
Title: Optimisation of a sustainable fuzzy EPQ inventory model using sextic equation
Abstract:
We develop a fuzzy EPQ inventory model to achieve sustainability and profit maximisation. Cost measures are included at every stage of the production and inventory process to handle carbon emissions safely. Fuzzy number representation of the input parameters helps to accommodate uncertainties in the inventory decision-making process. The fuzzy net profit function's ambiguity level determines the degree of uncertainty in the net profit. Descartes' rule of signs is used in a sextic equation to establish a solution to the optimal length of the production run. The numerical results show that increasing ambiguity in the fuzzy profit function will decrease the net profit. Accuracy in predicting production cost, setup cost, and annual demand is essential as the net profit is more sensitive to these parameters. A multivariate regression equation is fitted to estimate a possible crisp net profit from the corresponding fuzzy net profit for given demand and production rates. [Submitted: 15 June 2019; Accepted: 24 April 2021]
Journal: European J. of Industrial Engineering
Pages: 442-478
Issue: 4
Volume: 16
Year: 2022
Keywords: sustainability; EPQ inventory; trapezoidal fuzzy number; Descartes' rule of signs.
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Handle: RePEc:ids:eujine:v:16:y:2022:i:4:p:442-478
Template-Type: ReDIF-Article 1.0
Author-Name: S. Sindhuja
Author-X-Name-First: S.
Author-X-Name-Last: Sindhuja
Author-Name: P. Arathi
Author-X-Name-First: P.
Author-X-Name-Last: Arathi
Title: An economic order quantity model for Pareto distribution deterioration with linear demand under linearly time-dependent shortages
Abstract:
The inventory models for deteriorating items aim to reduce the total cost under normal market conditions. This paper focuses on the possible effects of minimising total cost by developing an economic order quantity (EOQ) model, where the deterioration is considered as Pareto distribution with linear demand. This model is applicable for vegetable vendors to make inventory decisions in the inventory system under the influence of optimal values. The linear demand and shortage of cost are also taken into consideration. To illustrate the proposed EOQ model, numerical examples and corresponding sensitivity analysis on the parameters <i>A</i>, <i>c</i>, <i>d</i>, <i>p<SUB align="right"><SMALL>c</SMALL></SUB></i>, <i>h</i>, <i>s</i>, <i>α</i> and <i>β</i> are discussed and compared with the existing models. The result of the model developed in this paper is based on the deterioration leading to significant effects of the Pareto distribution deterioration variables <i>α</i> and <i>β</i> on the 'total cost'. The complex algebraic equations are solved using MATLAB R2013a. [Submitted: 11 January 2021; Accepted: 12 April 2021]
Journal: European J. of Industrial Engineering
Pages: 418-441
Issue: 4
Volume: 16
Year: 2022
Keywords: economic order quantity; EOQ; Pareto distribution; deterioration; linear demand; shortage.
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Handle: RePEc:ids:eujine:v:16:y:2022:i:4:p:418-441
Template-Type: ReDIF-Article 1.0
Author-Name: Antoine Clement
Author-X-Name-First: Antoine
Author-X-Name-Last: Clement
Author-Name: Didier Gourc
Author-X-Name-First: Didier
Author-X-Name-Last: Gourc
Author-Name: Daouda Kamissoko
Author-X-Name-First: Daouda
Author-X-Name-Last: Kamissoko
Author-Name: Francois Marmier
Author-X-Name-First: Francois
Author-X-Name-Last: Marmier
Title: An original approach to assess the robustness of road freight transport plannings based on a dynamic risk identification
Abstract:
The road freight transport sector contributes significantly to the delivery of goods. Today, more than 90% of goods are conveyed using the road transport mode. In the same time, customers' requirements become more and more numerous and accurate, which increases the complexity of planner work. The aim of this work is to propose to planners robustness indicators measuring the chance the planned tour could respect the requirements. Based on a planning system giving several feasible daily schedules, our approach allows to dynamically identify the risks that could impact each planning and then simulate the influence of those risks on the plans' activities to assess the robustness indicators. They are composed of an indicator measuring the probability to respect the customers' requirements and two actionable data. These actionable data give to planners information on levers they could use to increase the robustness of the plan. [Submitted: 11 September 2020; Accepted: 27 April 2021]
Journal: European J. of Industrial Engineering
Pages: 479-505
Issue: 4
Volume: 16
Year: 2022
Keywords: risk identification; robustness; decision making; danger; daily schedule; road freight transport.
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Handle: RePEc:ids:eujine:v:16:y:2022:i:4:p:479-505
Template-Type: ReDIF-Article 1.0
Author-Name: Salah Haridy
Author-X-Name-First: Salah
Author-X-Name-Last: Haridy
Author-Name: Nger Ling Chong
Author-X-Name-First: Nger Ling
Author-X-Name-Last: Chong
Author-Name: Michael B.C. Khoo
Author-X-Name-First: Michael B.C.
Author-X-Name-Last: Khoo
Author-Name: Mohammad Shamsuzzaman
Author-X-Name-First: Mohammad
Author-X-Name-Last: Shamsuzzaman
Author-Name: Philippe Castagliola
Author-X-Name-First: Philippe
Author-X-Name-Last: Castagliola
Title: Synthetic control chart with curtailment for monitoring shifts in fraction non-conforming
Abstract:
The integration of the curtailment method with control charts considerably improves the detection speed by signalling an out-of-control condition prior to the inspection of the whole sample. To date, few research works have focused on the incorporation of the curtailment method to improve the performance of control charts. Thus, this paper incorporates the curtailment approach with the synthetic chart to propose a synthetic with curtailment (Curt_Syn) control chart for detecting upward shifts in the fraction non-conforming, <i>p</i>. We compare the newly developed Curt_Syn chart with the synthetic, exponentially weighted moving average (EWMA), cumulative sum (CUSUM), EWMA with curtailment (Curt_EWMA), and CUSUM with curtailment (Curt_CUSUM) charts. From an overall perspective, the results reveal that the Curt_Syn chart surpasses the synthetic chart by 38% under various conditions. For all <i>p</i> shifts, the Curt_Syn chart outperforms the CUSUM and EWMA charts. When the <i>p</i> shift is large, the Curt_Syn chart is superior to the Curt_CUSUM and Curt_EWMA charts. To demonstrate the implementation of the Curt_Syn chart, an illustrative example is provided. [Received: 30 April 2019; Accepted: 7 April 2021]
Journal: European J. of Industrial Engineering
Pages: 194-214
Issue: 2
Volume: 16
Year: 2022
Keywords: control chart; synthetic chart; curtailment; fraction non-conforming; quality control; statistical process control; SPC; monitoring; attribute chart.
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Handle: RePEc:ids:eujine:v:16:y:2022:i:2:p:194-214
Template-Type: ReDIF-Article 1.0
Author-Name: Woo-sung Kim
Author-X-Name-First: Woo-sung
Author-X-Name-Last: Kim
Author-Name: Kyungsu Park
Author-X-Name-First: Kyungsu
Author-X-Name-Last: Park
Title: Waiting time distribution in single-channel deterministic flow lines with discrete inter-arrival time distributions
Abstract:
Although previous studies proved that deterministic flow lines can be analysed separately by an exact decomposition method called a channel method and that the delay an item experiences in each machine possesses a Markovian property, the exact performance measures for the system with general arrival process cannot be obtained due to the lack of the results on relevant GI/D/1 queue. The solution obtained only for the system with specific arrival patterns such as geometric distribution or JIT arrivals considering setups. In this paper, exact decomposition methods are investigated through the systems consisting of one channel. Assuming general and discrete inter-arrival times, we introduce a procedure to calculate the equilibrium probabilities for waiting time distributions. It is demonstrated that probabilities can be computed by a matrix analytic method and recursions based on the decomposition methods. Inspired by the steel product manufacturing process, two-stage conveyor belt systems are analysed as an application. [Received: 28 July 2020; Accepted: 1 March 2021]
Journal: European J. of Industrial Engineering
Pages: 117-142
Issue: 2
Volume: 16
Year: 2022
Keywords: flow line model; stochastic modelling; Markov chain model; steel manufacturing system; tandem queue.
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Handle: RePEc:ids:eujine:v:16:y:2022:i:2:p:117-142
Template-Type: ReDIF-Article 1.0
Author-Name: Saeed Saemi
Author-X-Name-First: Saeed
Author-X-Name-Last: Saemi
Author-Name: Alireza Rashidi Komijan
Author-X-Name-First: Alireza Rashidi
Author-X-Name-Last: Komijan
Author-Name: Reza Tavakkoli-Moghaddam
Author-X-Name-First: Reza
Author-X-Name-Last: Tavakkoli-Moghaddam
Author-Name: Mohammad Fallah
Author-X-Name-First: Mohammad
Author-X-Name-Last: Fallah
Title: Solving an integrated mathematical model for crew pairing and rostering problems by an ant colony optimisation algorithm
Abstract:
The crew pairing problem (CPP) and the crew rostering problem (CRP) are two sub-problems of a crew scheduling problem (CSP). Solving these problems based on a sequential approach may not yield the optimum solution. Therefore, the present study aims to consider the integrated CPP and CRP and present a new mathematical formulation. Due to its NP-hardness complexity, a meta-heuristic algorithm based on ant colony optimisation (ACO) is designed and used to solve the integrated problem and sequential approach (CRP followed by CPP) in some test problems extracted from a data set. The solutions provided by ACO for the integrated problem show 21.64% cost reduction in a reasonable time increase in comparison with those obtained by the sequential approach. Also, the ACO algorithm can provide solutions with a 2.96% average gap to the optimal solutions (by the exact method) for small-sized problems. Also, the proposed integrated approach leads to solutions with the best/optimal number of crew members to be assigned. The findings indicate that the proposed ACO has an efficient performance in solving the integrated problem. [Received: 20 May 2020; Accepted: 8 April 2021]
Journal: European J. of Industrial Engineering
Pages: 215-240
Issue: 2
Volume: 16
Year: 2022
Keywords: crew pairing and crew rostering; crew scheduling; inseparable flights; ant colony optimisation; ACO.
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Handle: RePEc:ids:eujine:v:16:y:2022:i:2:p:215-240
Template-Type: ReDIF-Article 1.0
Author-Name: Ilkyeong Moon
Author-X-Name-First: Ilkyeong
Author-X-Name-Last: Moon
Author-Name: Won Young Yun
Author-X-Name-First: Won Young
Author-X-Name-Last: Yun
Author-Name: Biswajit Sarkar
Author-X-Name-First: Biswajit
Author-X-Name-Last: Sarkar
Title: Effects of variable setup cost, reliability, and production costs under controlled carbon emissions in a reliable production system
Abstract:
Although important for production industries to reach fully sustainable manufacturing processes, those implementing production systems face challenges in reaching this reliability goal. In this direction, a production system is modelled through a basic economic-production paradigm under carbon emissions with a storage constraint and demand-dependent unit production cost. More reliable production houses produce fewer defective products than the unreliable production system. As the model contains a power-function, a geometric programming procedure is employed to obtain a quasi-closed form of the optimal solution. A numerical example based on data from the literature and a case study based on industry data, are provided to demonstrate geometric programming as a valuable analytical tool to resolve this type of problem for a production system under carbon emissions. Finally, a sensitivity analysis and graphical illustration are provided to illustrate the model. Numerical results show that the production system becomes completely reliable when the recommended model is used. [Submitted: 18 May 2019; Accepted: 8 March 2021]
Journal: European J. of Industrial Engineering
Pages: 371-397
Issue: 4
Volume: 16
Year: 2022
Keywords: manufacturing systems; production design; geometric programming; inventory; variable production cost.
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Handle: RePEc:ids:eujine:v:16:y:2022:i:4:p:371-397
Template-Type: ReDIF-Article 1.0
Author-Name: Shih-Pin Chen
Author-X-Name-First: Shih-Pin
Author-X-Name-Last: Chen
Author-Name: Yu-Min Lin
Author-X-Name-First: Yu-Min
Author-X-Name-Last: Lin
Title: Inventory control for the closed-loop supply chain with technological progress and planned shortages
Abstract:
The impact of Industry 4.0 has received much attention in academic and practice fields. Therefore, understanding the effects of technological progress in production on closed-loop supply chain (CLSC) inventory management is critical. In view of profit efficiency, this paper investigates the effects of technological progress in production on inventory policies in a CLSC considering planned shortages. A CLSC production-inventory model is proposed to jointly determine sale and collection prices and production time points. The representative numerical results show that technological progress in manufacturing inconsistently has a positive impact on the NPU because the total quantity produced and cycle length vary. The impact of technological progress may be greater in the manufacturing process than in the remanufacturing process. The results can aid production managers in finding optimal production-inventory strategies considering technological progress and planned shortages. Additionally, the results provide useful information regarding the impact of technological progress in selecting investment targets. [Received: 5 August 2020; Accepted: 16 March 2021]
Journal: European J. of Industrial Engineering
Pages: 143-168
Issue: 2
Volume: 16
Year: 2022
Keywords: inventory; technological progress; remanufacturing; sequential quadratic programming; supply chain management; learning effects.
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Handle: RePEc:ids:eujine:v:16:y:2022:i:2:p:143-168
Template-Type: ReDIF-Article 1.0
Author-Name: Salih O. Duffuaa
Author-X-Name-First: Salih O.
Author-X-Name-Last: Duffuaa
Author-Name: Ahmed M. Ghaithan
Author-X-Name-First: Ahmed M.
Author-X-Name-Last: Ghaithan
Author-Name: Ahmed M. Attia
Author-X-Name-First: Ahmed M.
Author-X-Name-Last: Attia
Title: A mathematical model for the optimal robust design of cause selecting control charts
Abstract:
Cause selecting charts (CSC) are statistical control-charts for monitoring multiple sequential processes; in contrast, Shewhart control-charts are useful for monitoring independent processes. The economic-statistical design of CSC involves the selection of the optimal design parameters that include the width of the chart, sample size, and sampling interval. The application of economic-statistical criteria is a well-established and active research field. However, these design approaches may not be reliable for a dynamic production environment due to the uncertainty associated with the values of the model parameters. The purpose of this paper is to develop a robust economic-statistical model for the design of CSC. The model is intended to minimise the risk associated with the incidence of different scenarios in a real production environment. Through the use of examples and sensitivity analysis, it is demonstrated that the model provides design parameters that are more sensitive to shifts, protect against the occurrence of other scenarios, and results in charts with a higher power. [Received: 21 July 2018; Accepted: 24 March 2021]
Journal: European J. of Industrial Engineering
Pages: 169-193
Issue: 2
Volume: 16
Year: 2022
Keywords: quality; cause selecting chart; CSC; control charts; robust design; dependent processes.
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Handle: RePEc:ids:eujine:v:16:y:2022:i:2:p:169-193
Template-Type: ReDIF-Article 1.0
Author-Name: Jie Lian
Author-X-Name-First: Jie
Author-X-Name-Last: Lian
Author-Name: ChenGuang Liu
Author-X-Name-First: ChenGuang
Author-X-Name-Last: Liu
Author-Name: Wenjuan Li
Author-X-Name-First: Wenjuan
Author-X-Name-Last: Li
Author-Name: Juning Su
Author-X-Name-First: Juning
Author-X-Name-Last: Su
Author-Name: Hongquan Xue
Author-X-Name-First: Hongquan
Author-X-Name-Last: Xue
Title: Task dispatching in reconfigurable seru production systems to minimise total earliness and tardiness
Abstract:
Owing to movable workstations, light equipment and multi-skilled workers, <i>serus</i> can be constructed, modified and dismantled rapidly. Taking over such an advantage, <i>serus</i> can be reconfigured in response to frequent changes in product types. The issue is how to arrange the configuration of <i>seru</i> with the tasks assigned to it. To this end, we focus on solving the task dispatching, product sequencing and <i>seru</i> reconfiguration problems simultaneously. A nonlinear mathematical model with objective of minimising the total earliness and tardiness is formulated. In order to verify the proposed model, small-size numerical examples are solved by Lingo. A genetic algorithm is developed due to its NP-hardness, and the algorithm is tested by numerical examples in different sizes. Based on the computational results, the performance of <i>seru</i> production systems and assembly lines is compared, and the impact of parameters on system performance is analysed. [Submitted: 6 January 2020; Accepted: 4 April 2021]
Journal: European J. of Industrial Engineering
Pages: 241-267
Issue: 3
Volume: 16
Year: 2022
Keywords: seru production; cell loading; seru reconfiguration; product sequencing; genetic algorithm.
File-URL: http://www.inderscience.com/link.php?id=121959
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Handle: RePEc:ids:eujine:v:16:y:2022:i:3:p:241-267
Template-Type: ReDIF-Article 1.0
Author-Name: Sweety Hansuwa
Author-X-Name-First: Sweety
Author-X-Name-Last: Hansuwa
Author-Name: Usha Mohan
Author-X-Name-First: Usha
Author-X-Name-Last: Mohan
Author-Name: Viswanath Kumar Ganesan
Author-X-Name-First: Viswanath Kumar
Author-X-Name-Last: Ganesan
Title: Scenario-based stochastic shelter location-allocation problem with vulnerabilities for disaster relief network design
Abstract:
We formulate the shelter location-allocation problem considering the vulnerability of the demand locations and their network connectivities with the shelter locations for disaster management's preparedness and response phase. We propose a scenario-based stochastic model that assigns the set of candidate locations evaluating operational, budgetary limitations, and service level expectations. The solution presents an evacuee-allocation plan considering the best collection of less vulnerable network connectivities between the demand areas and the shelter locations. We present a linear relaxation heuristic and compare the heuristic performance with the scenario-based formulation solved using CPLEX 12.8 optimisation solver for various problem sizes. We finally apply and solve the problem using real-life case data obtained during the major flooding event in and around the Chennai Metropolitan Development Area during 2015 to present our model's applicability and emergency response requirements. [Submitted: 12 November 2020; Accepted: 19 April 2021]
Journal: European J. of Industrial Engineering
Pages: 507-530
Issue: 5
Volume: 16
Year: 2022
Keywords: disaster management; shelter location-allocation; stochastic programming; linear relaxation heuristic.
File-URL: http://www.inderscience.com/link.php?id=125296
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Handle: RePEc:ids:eujine:v:16:y:2022:i:5:p:507-530
Template-Type: ReDIF-Article 1.0
Author-Name: Eduardo García-Escribano
Author-X-Name-First: Eduardo
Author-X-Name-Last: García-Escribano
Author-Name: Adolfo López-Paredes
Author-X-Name-First: Adolfo
Author-X-Name-Last: López-Paredes
Author-Name: Javier Pajares
Author-X-Name-First: Javier
Author-X-Name-Last: Pajares
Title: An empirical analysis of the effect of customising project management tools and techniques on industrial SMEs' project success
Abstract:
Project managers have access to many tools and techniques to plan, monitor, and control their projects. However, not all of these project management tools and techniques (PMTT) are suited to the management of projects in all contexts and they may need to be customised or adjusted from the standard methodologies. The paper presents a comprehensive study with a duration of almost three years that used several research methods to answer the research questions posed. The study was made in 35 small and medium enterprises (SMEs), involving 94 projects in total and 54 project managers, focused on the manufacturing, healthcare, and telecommunications sectors. Although the results cannot be generalised, it is an interesting contribution relating to the tailoring of PMTT in SMEs and its correlation with a set of key performance indicators (KPIs) that measure project management performance. [Submitted: 22 February 2021; Accepted: 9 May 2021]
Journal: European J. of Industrial Engineering
Pages: 531-555
Issue: 5
Volume: 16
Year: 2022
Keywords: empirical analysis; project management tools and techniques; PMTT; project success; project management standard methodologies; project monitoring; industrial SMEs; key performance indicators; KPIs; small and medium enterprises; SMEs.
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Handle: RePEc:ids:eujine:v:16:y:2022:i:5:p:531-555
Template-Type: ReDIF-Article 1.0
Author-Name: Hela Moalla Frikha
Author-X-Name-First: Hela Moalla
Author-X-Name-Last: Frikha
Author-Name: Ahmed Frikha
Author-X-Name-First: Ahmed
Author-X-Name-Last: Frikha
Title: An improved AHP approach to select appropriate location sites for infectious medical waste disposal companies
Abstract:
Nowadays, infectious healthcare waste management has become a challenging task for the municipal authorities especially in developing countries including Tunisia, which considers this concern as one of the environmental priorities. Since these wastes have resistant impacts on public health and the deleterious effects on the environment, government authorities have deployed efforts to improve healthcare waste management. Locating infectious healthcare disposal firms is a sophisticated multi-criteria decision-making problem, which requires a compromise solution chosen according to conflicting criteria. This paper addresses the use of a modified analytic hierarchy process approach to select objectively the best sites for installing infectious healthcare waste disposal firms in Tunisia. A number of criteria and their sub-criteria are considered, several locations are evaluated, and the most appropriate ones are selected. Moreover, using expert choice software, sensitivity analysis is performed to show how sensitive the results are to the removal of one or more criteria. [Submitted: 21 January 2021; Accepted: 27 June 2021]
Journal: European J. of Industrial Engineering
Pages: 618-649
Issue: 5
Volume: 16
Year: 2022
Keywords: decision analysis; multiple criteria decision aid; waste disposal firm; infectious healthcare waste management; location problem; analytic hierarchy process.
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Handle: RePEc:ids:eujine:v:16:y:2022:i:5:p:618-649
Template-Type: ReDIF-Article 1.0
Author-Name: Sana Frifita
Author-X-Name-First: Sana
Author-X-Name-Last: Frifita
Author-Name: Hasan Murat Afsar
Author-X-Name-First: Hasan Murat
Author-X-Name-Last: Afsar
Author-Name: Faicel Hnaien
Author-X-Name-First: Faicel
Author-X-Name-Last: Hnaien
Title: An efficient mat-heuristic algorithm for the dynamic disassembly assembly routing problem with returns
Abstract:
We study a static and dynamic disassembly assembly routing problem with returns (2D-ARP-R). The problem presents the case where a set of disassembled components and raw materials are converted into a final product. By regrouping production and routing decisions, it is possible to synchronise different activities (assembly, disassembly, inventory management, and vehicle routing) and build a global optimal solution. A mixed integer linear programming (MILP) is presented to solve this new variant. A mat-heuristic based on integer programming and variable neighborhood search algorithm (VNS) is also developed to solve the larger size instances. Numerical results show that the mat-heuristic approach improves the upper bounds obtained by CPLEX in a much shorter time, in most cases. We also evaluate the benefits of coordination of the production and routing decisions within the same optimisation model. This benefit can reach up to 117.38% compared to the hierarchical approach. [Submitted: 4 April 2020; Accepted: 27 June 2021]
Journal: European J. of Industrial Engineering
Pages: 584-617
Issue: 5
Volume: 16
Year: 2022
Keywords: supply chain management; assembly routing problem; ARP; disassembly problem; returns; mat-heuristic.
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Handle: RePEc:ids:eujine:v:16:y:2022:i:5:p:584-617
Template-Type: ReDIF-Article 1.0
Author-Name: Tao Zhou
Author-X-Name-First: Tao
Author-X-Name-Last: Zhou
Author-Name: Kai Li
Author-X-Name-First: Kai
Author-X-Name-Last: Li
Author-Name: Shan-Lin Yang
Author-X-Name-First: Shan-Lin
Author-X-Name-Last: Yang
Title: Remanufacturing with material restrictions in monopoly and duopoly
Abstract:
In this paper, we study firms' pricing and competitive strategies. We discuss a monopolistic scenario with an original supplier (OS) and a duopolistic scenario with an additional independent supplier (IS). Moreover, we investigate the effects of manufacturing cost, remanufacturing cost, customer discount factor, acquisition rate and the entry of a competitor on OS's strategies. Our results show that, in monopoly, the OS's remanufacturing possibility does not always increase in customer discount factor. Moreover, a lower manufacturing cost promotes complementary relationships between new and remanufactured products. In duopoly, a lower manufacturing cost reduces the remanufacturing possibility of the IS. Furthermore, raising the price of a remanufactured product may not reduce the consumer demand. The proposed model can be applied to many industries where the managers have the full awareness of extended producer responsibility, and they are willing to engage in the project related to remanufacturing. [Submitted: 2 January 2020; Accepted: 6 June 2021]
Journal: European J. of Industrial Engineering
Pages: 556-583
Issue: 5
Volume: 16
Year: 2022
Keywords: remanufacturing; material restrictions; monopoly; duopoly; pricing.
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Handle: RePEc:ids:eujine:v:16:y:2022:i:5:p:556-583
Template-Type: ReDIF-Article 1.0
Author-Name: Elham Shadkam
Author-X-Name-First: Elham
Author-X-Name-Last: Shadkam
Title: A novel two-phase algorithm for a centralised production planning problem by symmetric weighted DEA approach: a case study in energy efficiency
Abstract:
This paper proposes a novel two-phase algorithm for a centralised production planning problem that covers both long-term and mid-term planning simultaneously. Mid-term decisions (first phase) include determining the amount of new inputs and outputs of units in the next production period and long-term decisions (second phase) are related to planning to create a new efficient production unit. The first phase includes a data envelopment analysis approach with symmetric weights through the penalty function. The second phase includes combining data envelopment analysis and response surface methods. In order to evaluate the proposed method, the National Iranian Gas Company is considered as a real case problem. The results show the superiority of the algorithm in both phases over similar methods. The main advantage of the first phase is the realistic production plan. Also, the main advantage of the second phase is optimising the response surface functions and maximising the efficiency of the unit at the same time using one model. [Submitted: 18 March 2021; Accepted: 27 September 2021]
Journal: European J. of Industrial Engineering
Pages: 732-756
Issue: 6
Volume: 16
Year: 2022
Keywords: production planning; symmetric weighted approach; data envelopment analysis; DEA; response surface method; gas company.
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Handle: RePEc:ids:eujine:v:16:y:2022:i:6:p:732-756
Template-Type: ReDIF-Article 1.0
Author-Name: Mehmet Alegoz
Author-X-Name-First: Mehmet
Author-X-Name-Last: Alegoz
Title: Simultaneous remanufacturing and government incentives in remanufacturing systems
Abstract:
Remanufacturing has been receiving a growing attention in both academia and industry due to its economic and environmental benefits. This study investigates the effects of simultaneous remanufacturing, i.e., the effects of entrance of an actor to remanufacturing business when there is already one actor making remanufacturing. To this end, three remanufacturing systems are considered as only the manufacturer remanufactures (case 1), only the retailer remanufactures (case 2) and both the manufacturer and the retailer simultaneously remanufacture (case 3) the used products. Stackelberg Game models are proposed for each of these cases and the performances of the actors are compared. The role of the government in remanufacturing systems is also investigated and the question, to whom should the government provide incentives in order to maximise the remanufactured product quantity, is discussed. Computational results bring various managerial insights regarding the simultaneous remanufacturing decisions of the actors and the role of the government. [Submitted: 1 May 2021; Accepted: 4 October 2021]
Journal: European J. of Industrial Engineering
Pages: 757-781
Issue: 6
Volume: 16
Year: 2022
Keywords: remanufacturing; competition; government incentive; closed-loop supply chain.
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Handle: RePEc:ids:eujine:v:16:y:2022:i:6:p:757-781
Template-Type: ReDIF-Article 1.0
Author-Name: Seong Wook Hwang
Author-X-Name-First: Seong Wook
Author-X-Name-Last: Hwang
Author-Name: Sunghoon Lim
Author-X-Name-First: Sunghoon
Author-X-Name-Last: Lim
Title: The charging infrastructure design problem with electric taxi demand prediction using convolutional LSTM
Abstract:
The authors present a charging infrastructure design problem with electric taxi demand prediction. Due to environmental concerns, electric vehicle adoption has significantly increased in the transportation sector. However, the use of electric vehicles is not highly commercialised in the taxi industry, because the immature charging network and frequent charging decrease taxi revenue efficiency. Therefore, charging infrastructure needs to be built in urban areas in consideration of operational requirements of the taxi industry. The authors first design a convolutional long short-term memory model that predicts taxi demand, along with hotspots. Then, based on the predicted taxi demand in hotspots, a mixed integer linear programming model is proposed to optimise the location of recharging stations to minimise the cost of locating stations and charging service. Also, we propose a heuristic algorithm to solve realistic and practical problems. Lastly, a case study is presented to validate the proposed research. [Submitted: 28 April 2021; Accepted: 5 September 2021]
Journal: European J. of Industrial Engineering
Pages: 651-678
Issue: 6
Volume: 16
Year: 2022
Keywords: OR in service industries; transportation; heuristics; machine learning; artificial intelligence.
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Handle: RePEc:ids:eujine:v:16:y:2022:i:6:p:651-678
Template-Type: ReDIF-Article 1.0
Author-Name: Yanyan Wang
Author-X-Name-First: Yanyan
Author-X-Name-Last: Wang
Author-Name: Rongjun Man
Author-X-Name-First: Rongjun
Author-X-Name-Last: Man
Author-Name: Wanmeng Zhao
Author-X-Name-First: Wanmeng
Author-X-Name-Last: Zhao
Title: Layout optimisation of fishbone robotic mobile fulfilment system
Abstract:
Robotic mobile fulfilment system (RMFS) heavily influences all traditional scheduling problems when operating a warehouse. Rack layout affects the efficiency of inbound and outbound and the utilisation ratio of storage. This paper focuses on analysing the compatibility between fishbone storage layout and RMFS and its equipment kinetic characteristics, such as movement velocity and acceleration. By building the equipment kinetic functions and subsequently simulating various fishbone storage layout solutions features by length-to-width ratio, storage volume, and rack size, this research analyses the relationship between inbound/outbound efficiency and warehouse space utilisation. The applicability range of fishbone rack layout is obtained by comparing conventional layout with different rack size. Meanwhile, energy consumption is of great significance to reduce warehousing operating costs and improve operational efficiency. Therefore, the impacts on inbound/outbound efficiency and energy consumption from velocity and acceleration are investigated. Results show that optimal velocity ranges between 1.5 m/s and 2 m/s and the optimal acceleration ranges between 0.2 m/s<SUP align="right"><SMALL>2</SMALL></SUP> and 0.25 m/s<SUP align="right"><SMALL>2</SMALL></SUP>. Too high acceleration or velocity is easy to cause congestion and deadlock, which is not easy to schedule. Overall, this research provides decision support for parts-to-picker system design. [Submitted: 19 March 2021; Accepted: 22 September 2021]
Journal: European J. of Industrial Engineering
Pages: 706-731
Issue: 6
Volume: 16
Year: 2022
Keywords: robotic mobile fulfilment system; RMFS; fishbone layout; layout optimisation.
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Handle: RePEc:ids:eujine:v:16:y:2022:i:6:p:706-731
Template-Type: ReDIF-Article 1.0
Author-Name: Junfei Ding
Author-X-Name-First: Junfei
Author-X-Name-Last: Ding
Author-Name: Weida Chen
Author-X-Name-First: Weida
Author-X-Name-Last: Chen
Title: Effects of trade credit insurance on remanufacturing decisions under carbon tax and emissions abatement
Abstract:
This study examines the impacts of trade credit insurance on the optimal decisions of the firm that remanufactures used products and implements emissions abatement strategy under carbon tax policy. In the presence of revenue loss risks generated by uncertain factors in the trading process with channel partners, a remanufacturing production decision-making model without trade credit insurance is firstly proposed as a benchmark, and then the trade credit insurance is integrated into the model to alleviate risk. Subsequently, the optimal decisions for the two models are derived and the optimal emissions abatement rates for different objectives are characterised. Through analysis and numerical examples, the results show that the firm has an incentive to increase remanufacturing quantity and is better off with the use of trade credit insurance, regardless of whether the firm conducts emissions abatement strategy. The emissions abatement strategy is unable to maximise the production quantity, the insurance coverage quantity and the firm's expected profit simultaneously. Additionally, although a high carbon tax decreases the firm's profit, it motivates the firm to direct increasing efforts toward reducing emissions. [Submitted: 2 December 2020; Accepted: 20 September 2021]
Journal: European J. of Industrial Engineering
Pages: 679-705
Issue: 6
Volume: 16
Year: 2022
Keywords: decision making; trade credit insurance; emissions abatement; remanufacturing; insurance premium rate.
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Handle: RePEc:ids:eujine:v:16:y:2022:i:6:p:679-705