Heuristic algorithms for truck scheduling of cross-docking operations in cold-chain logistics

ABSTRACT

Nowadays cross-docking operations play a significant role in the cold-chain logistics. This paper addresses the cold-chain cross-docking truck scheduling problem where two types of products, i.e. refrigerated and frozen ones, demand separate trucks and storage areas with distinct temperature settings during their storage and transportation. We present a mixed-integer linear programming model with the objective of minimising the total operational costs that consist of inbound truck arrival penalties for violating contracted time windows, product delivery tardiness penalties, inventory costs and outbound truck transportation costs. Due to the strong NP-hardness of the considered problem, we solve it in two phases where the inbound truck arrival schedule and the schedule of outbound truck departure together with product processing are produced, respectively. Four heuristic algorithms are proposed to generate complete solutions of the considered two-stage problem, which are the combinations of two solution frameworks for the first stage and two methods for the second stage. Computational experiments are carried out to verify the effectiveness and efficiency of the proposed heuristic algorithms in terms of the solution quality and running time, respectively.

Keywords:

• Truck scheduling
• cross-docking terminal
• cold-chain logistics
• heuristic algorithm
• combinatorial optimization

Acknowledgments

The authors are grateful to the editor and anonymous reviewers for their suggestions in improving the quality of the manuscript. This work was financially supported by the National Natural Science Foundation of China (71771048, 71832001, 71571134 and 71531011) and the Fundamental Research Funds for the Central Universities (2232018H-07).

Disclosure statement

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

Additional information

Funding

This work was financially supported by the National Natural Science Foundation of China [grant numbers 71771048, 71832001, 71571134 and 71531011] and the Fundamental Research Funds for the Central Universities [grant number 2232018H-07].

Notes on contributors

Feifeng Zheng

Feifeng Zheng received the B.S. degree in information management, the M.S. degree in management science and engineering and the Ph.D. degree in management science and engineering from Xi'an Jiaotong University, Xi'an, China, in 1998, 2003 and 2006. He is a Professor in Donghua University, Shanghai. His research interests include production scheduling and container terminal resource scheduling.

Yaxin Pang

Yaxin Pang received the B.S. degree in management science and engineering from Donghua University, Shanghai, China, in 2018. She is a master student at Donghua University, majoring in Management science and engineering. Her interests include production scheduling and logistics optimisation.

Yinfeng Xu

Yinfeng Xu received the B.S. degree in applied mathematics, the M.S. degree in computational mathematics and the Ph.D. degree in operational research and control from Jilin University of Technology, Xi'an Jiaotong and Chinese Academy of Sciences, respectively, in 1983, 1988 and 1992. He is a Professor in Donghua University, Shanghai. His research interests include production scheduling and combinatorial optimisation.

Ming Liu

Ming Liu received the B.S. degree in management science and engineering and the Ph.D. degree in management science and engineering from Xi'an Jiaotong University, Xi'an, China, in 2005 and 2010. He is an Associate Professor in Tongji University, Shanghai. His research interests include logistics optimisation and production scheduling.