Multi-Period Distribution Network Design with Boundedly Rational Customers for the Service-Oriented Manufacturing Supply Chain: A 4PL Perspective

11月 11, 2022·
Yuxin Zhang
,
Zheming Gao
,
Min Huang*
Songchen Jiang
Songchen Jiang
,
Mingqiang Yin
,
Shu-Cherng Fang
· 0 分钟阅读时长
摘要
With the service level playing an increasingly essential role in the service-oriented manufacturing (SOM) supply chain, the distribution network design can be heavily affected by the customer behaviour based on their satisfaction of services. In this paper, we consider the service level for service time and delivery quantity separately. A novel mixed integer non-linear programming model is proposed to design the multi-period distribution network from a fourth-party logistics (4PL) perspective. The customer satisfaction based on prospect theory is maximised while considering the investment budget and the service level. A scenario-based linear reformulation is proposed to find the optimal solution when the problem scale is small. For a large-scale problem, we propose an individual-driven Q-learning based memetic particle swarm optimisation algorithm. Numerical experiments are conducted to demonstrate the effectiveness and efficiency of the proposed algorithm. Furthermore, the impact of service modes, different customer behaviour, and customer satisfaction evaluation periods on distribution network is investigated. We find that the length of evaluation periods leads to differences in customer satisfaction due to different perceptions of ‘small loss’ and ‘big gain’ by boundedly rational customers.
类型
出版物
International Journal of Production Research
publications
Songchen Jiang
Authors
Assistant Professor
I will soon join the School of Management at Xi’an Jiaotong University. I received my Ph.D. degree from the College of Information Science and Engineering at Northeastern University, China, under the supervision of Prof. Min Huang. During my doctoral studies, I was also a visiting Ph.D. student at the Institute of Operations Research and Analytics, National University of Singapore, supervised by Prof. Chung-Piaw Teo. My research focuses on data-driven optimization, distributionally robust optimization, and stochastic modeling, with applications in supply chain management, such as inventory optimization, supply chain network design, logistics planning.