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

Abstract

Urged 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 routing
• perishable food
• integer linear programme
• multi-type RTIs
• kernel search matheuristic

Acknowledgements

This 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 statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data that support the findings of this study are available from the corresponding author Ada Che, Email: [email protected], upon reasonable request.

Additional information

Funding

This 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 contributors

Yipei Zhang

Yipei 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 Chu

Feng 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 Che

Ada 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 Li

Yantong 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.