Closed-loop inventory routing problem for perishable food with returnable transport items selection

IF 7 2区 工程技术 Q1 ENGINEERING, INDUSTRIAL International Journal of Production Research Pub Date : 2023-11-02 DOI:10.1080/00207543.2023.2275639
Yipei Zhang, Feng Chu, Ada Che, Yantong Li
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A real CIRP with multi-type RTIs for fresh strawberries is used to demonstrate the practicality of the ILP. For this case study, we perform extensive sensitivity analysis of the relevant parameters, extracting valuable managerial insights. Finally, experiments are conducted on 170 randomly generated instances. Computational results show that the proposed KS manages to achieve competitive solutions for instances with up to 10 retailers much more efficiently than CLPEX. For instances with up to 40 retailers, the KS algorithm significantly outperforms CPLEX in terms of solution quality, improving the obtained profit by 80.03% on average under the same computational time.KEYWORDS: Closed-loop inventory routingperishable foodinteger linear programmemulti-type RTIskernel search matheuristic AcknowledgementsThis work was partially derived from the first author’s Doctoral dissertation ‘Zhang, Y. (2019). Optimisation of closed-loop food supply chain with returnable transport items (Doctoral dissertation, University of Paris-Saclay; Northwestern Polytechnical University, Xi'an (China))’.Disclosure statementNo potential conflict of interest was reported by the author(s).Data availability statementThe data that support the findings of this study are available from the corresponding author Ada Che, Email: ache@nwpu.edu.cn, upon reasonable request.Additional informationFundingThis work was partially supported by the National Natural Science Foundation of China [grant numbers 72201040, 72310107003 and 72271201], the China Postdoctoral Science Foundation [grant number 2021M700527], the Youth Innovation Team of Shaanxi Universities [grant number 22JP003], and the Fundamental Research Funds for the Central Universities [grant number 300102232607]. The authors also wish to thank all anonymous reviewers whose constructive comments helped to improve this paper.Notes on contributorsYipei ZhangYipei Zhang received the M.S. degree in management science and engineering from Northwestern Polytechnical University, Xi’an, China, in 2015, and the Ph.D. degrees from the University of Paris Saclay, Paris, France, and Northwestern Polytechnical University, Xi’an, China, in 2019 and 2020.Dr. Zhang is currently a Lecturer with Chang’an University. She has authored or coauthored articles published in International Journal of Production Research, Computers & Industrial Engineering, Journal of Enterprise Information Management, IEEE Transactions on Intelligent Transportation Systems, and IEEE Transactions on Engineering Management. Her research interests include operations research, closed-loop supply chain optimisation, and project portfolio optimisation.Feng ChuFeng Chu is currently a Full Professor of Operations Research at University of Evry and University of Paris-Saclay, France and leader of the Algorithmic, Operations Research, Bioinformatics and Statistical learning group. She has authored or coauthored over 200 articles in international journals, such as IEEE Transactions on ITS, SMC and TASE, European Journal of Operational Research, Computers & Operations Research, International Journal of Production Research, International Journal of Production Economics, Omega-The International Journal of Management Science, and Decision Support Systems. Her research interests include operations research, multi-objective optimisation, stochastic programming, petri nets, logistics, mobility, planning, scheduling, and supply chain risk management.Dr. Chu was an Associate Editor for IEEE T-SMC, Part C from 2010 to 2013. She is currently an Associate Editor for IEEE T-ITS, IEEE TASE and IJPR. She is an IPC member for over 100 international conferences.Ada CheAda Che (Senior Member, IEEE) received the B.S. and Ph.D. degrees in Mechanical Engineering from Xi'an Jiaotong University, Xi'an, China, in 1994 and 1999, respectively. Since 2005, he has been a Professor with Northwestern Polytechnical University, Xi'an. 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Dr. Che is currently serving as an Associate Editor for the IEEE Transactions on Intelligent Transportation Systems and Journal of Industrial and Management Optimization.Yantong LiYantong Li received the B.S. degree in traffic and transportation from Beijing Jiaotong University, Beijing, China, in 2011, the M.S. degree in transportation planning and management from Military Transportation University, Tianjin, China, in 2013, and the Ph.D. degree in Automation from the University of Paris Saclay, Evry, France, in 2019.Dr. Li is an Associate Professor at Dalian Maritime University, Dalian, China. His research interests include planning and scheduling in production and logistics systems, integrated optimisation in supply chain, smart logistics, and mathematical programming-based methods. 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Abstract

AbstractUrged by the necessity to establish sustainable supply chains (SCs), this study focuses on exploring the closed-loop inventory routing problem (CIRP) for perishable food packed by multi-type returnable transport items (RTIs). The selling revenue of perishable food is dependent on food's remaining shelf life and the specific type of RTIs used for packaging. RTI selection decisions need to be jointly considered in the CIRP to weigh the potential benefits against associated costs. For this problem, we first develop an integer linear programme (ILP) to maximise the total profit of the holistic SC. Subsequently, we design a tailored kernel search (KS) matheuristic as an efficient solution. A real CIRP with multi-type RTIs for fresh strawberries is used to demonstrate the practicality of the ILP. For this case study, we perform extensive sensitivity analysis of the relevant parameters, extracting valuable managerial insights. Finally, experiments are conducted on 170 randomly generated instances. Computational results show that the proposed KS manages to achieve competitive solutions for instances with up to 10 retailers much more efficiently than CLPEX. For instances with up to 40 retailers, the KS algorithm significantly outperforms CPLEX in terms of solution quality, improving the obtained profit by 80.03% on average under the same computational time.KEYWORDS: Closed-loop inventory routingperishable foodinteger linear programmemulti-type RTIskernel search matheuristic AcknowledgementsThis work was partially derived from the first author’s Doctoral dissertation ‘Zhang, Y. (2019). Optimisation of closed-loop food supply chain with returnable transport items (Doctoral dissertation, University of Paris-Saclay; Northwestern Polytechnical University, Xi'an (China))’.Disclosure statementNo potential conflict of interest was reported by the author(s).Data availability statementThe data that support the findings of this study are available from the corresponding author Ada Che, Email: ache@nwpu.edu.cn, upon reasonable request.Additional informationFundingThis work was partially supported by the National Natural Science Foundation of China [grant numbers 72201040, 72310107003 and 72271201], the China Postdoctoral Science Foundation [grant number 2021M700527], the Youth Innovation Team of Shaanxi Universities [grant number 22JP003], and the Fundamental Research Funds for the Central Universities [grant number 300102232607]. The authors also wish to thank all anonymous reviewers whose constructive comments helped to improve this paper.Notes on contributorsYipei ZhangYipei Zhang received the M.S. degree in management science and engineering from Northwestern Polytechnical University, Xi’an, China, in 2015, and the Ph.D. degrees from the University of Paris Saclay, Paris, France, and Northwestern Polytechnical University, Xi’an, China, in 2019 and 2020.Dr. Zhang is currently a Lecturer with Chang’an University. She has authored or coauthored articles published in International Journal of Production Research, Computers & Industrial Engineering, Journal of Enterprise Information Management, IEEE Transactions on Intelligent Transportation Systems, and IEEE Transactions on Engineering Management. Her research interests include operations research, closed-loop supply chain optimisation, and project portfolio optimisation.Feng ChuFeng Chu is currently a Full Professor of Operations Research at University of Evry and University of Paris-Saclay, France and leader of the Algorithmic, Operations Research, Bioinformatics and Statistical learning group. She has authored or coauthored over 200 articles in international journals, such as IEEE Transactions on ITS, SMC and TASE, European Journal of Operational Research, Computers & Operations Research, International Journal of Production Research, International Journal of Production Economics, Omega-The International Journal of Management Science, and Decision Support Systems. Her research interests include operations research, multi-objective optimisation, stochastic programming, petri nets, logistics, mobility, planning, scheduling, and supply chain risk management.Dr. Chu was an Associate Editor for IEEE T-SMC, Part C from 2010 to 2013. She is currently an Associate Editor for IEEE T-ITS, IEEE TASE and IJPR. She is an IPC member for over 100 international conferences.Ada CheAda Che (Senior Member, IEEE) received the B.S. and Ph.D. degrees in Mechanical Engineering from Xi'an Jiaotong University, Xi'an, China, in 1994 and 1999, respectively. Since 2005, he has been a Professor with Northwestern Polytechnical University, Xi'an. He is the author or coauthor of nearly 60 articles in international journals, such as Omega, Naval Research Logistics, Computers & Operations Research, IEEE Transactions on Robotics and Automation, International Journal of Production Research, European Journal of Operational Research, Operations Research Letters, and International Journal of Production Economics. His research interests include transportation planning and optimisation, production scheduling, and system modelling and optimisation. Dr. Che is currently serving as an Associate Editor for the IEEE Transactions on Intelligent Transportation Systems and Journal of Industrial and Management Optimization.Yantong LiYantong Li received the B.S. degree in traffic and transportation from Beijing Jiaotong University, Beijing, China, in 2011, the M.S. degree in transportation planning and management from Military Transportation University, Tianjin, China, in 2013, and the Ph.D. degree in Automation from the University of Paris Saclay, Evry, France, in 2019.Dr. Li is an Associate Professor at Dalian Maritime University, Dalian, China. His research interests include planning and scheduling in production and logistics systems, integrated optimisation in supply chain, smart logistics, and mathematical programming-based methods. His research papers are published or accepted by some international journals, including INFORMS Journal on Computing, European Journal of Operational Research, International Journal of Production Research, Transportation Research – Part E, Omega, International Journal of Production Economics, IEEE Transactions on Automation Science and Engineering, IEEE Transactions on Intelligent Transportation Systems, IEEE Transactions on Engineering Management, and Computers & Operations Research.
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具有可退货运输物品选择的易腐食品闭环库存路径问题
他在Omega、Naval Research Logistics、Computers & Operations Research、IEEE Transactions on Robotics and Automation、international Journal of Production Research、European Journal of Operational Research、Operations Research Letters和international Journal of Production Economics等国际期刊上发表了近60篇文章。他的研究兴趣包括运输规划和优化、生产调度、系统建模和优化。他目前担任IEEE Transactions on Intelligent Transportation Systems和Journal of Industrial and Management Optimization的副主编。李彦彤于2011年获得北京交通大学交通与运输专业学士学位,2013年获得中国天津军事运输大学交通规划与管理专业硕士学位,2019年获得法国巴黎萨克雷大学自动化专业博士学位。他是中国大连海事大学的副教授。他的研究兴趣包括生产和物流系统的计划和调度、供应链的集成优化、智能物流和基于数学规划的方法。他的研究论文被INFORMS Journal on Computing、European Journal of Operational research、international Journal of Production research、Transportation research Part E、Omega、international Journal of Production Economics、IEEE Transactions on Automation Science and Engineering、IEEE Transactions on Intelligent Transportation Systems、IEEE Transactions on Engineering Management、Computers & Operations research等国际期刊发表或接受。
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来源期刊
International Journal of Production Research
International Journal of Production Research 管理科学-工程:工业
CiteScore
19.20
自引率
14.10%
发文量
318
审稿时长
6.3 months
期刊介绍: The International Journal of Production Research (IJPR), published since 1961, is a well-established, highly successful and leading journal reporting manufacturing, production and operations management research. IJPR is published 24 times a year and includes papers on innovation management, design of products, manufacturing processes, production and logistics systems. Production economics, the essential behaviour of production resources and systems as well as the complex decision problems that arise in design, management and control of production and logistics systems are considered. IJPR is a journal for researchers and professors in mechanical engineering, industrial and systems engineering, operations research and management science, and business. It is also an informative reference for industrial managers looking to improve the efficiency and effectiveness of their production systems.
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