Multi-objective optimization of the auto-carrier loading and routing problem in an automotive logistics company

Abstract

This paper presents a real-world auto-carrier loading and routing problem encountered by an automotive logistics company in China. The problem requires determining a set of routes for auto-carriers to transport vehicles from warehouses to dealers subject to several loading and routing constraints. Four objectives are considered, including the maximization of the number of loaded urgent vehicles and the number of loaded vehicles, and the minimization of the number of visits to dealers and travel distance. To solve such a multi-objective problem, we develop a two-stage iterated local search heuristic with the lexicographic optimization principle. Expressly, we assume that all vehicles are stored in one warehouse and solve the resulting problem as the first stage. Then the best-found solution is improved by considering the multiple warehouse constraints in the second stage. The effectiveness of the proposed heuristic is validated by comparing it with a commercial solver and the company’s approach. Moreover, computational results provide managerial insights for decision-makers when considering the objectives and their priorities in different scenarios.

Keywords:

• Vehicle routing
• auto-carrier transportation
• lexicographic optimization
• iterated local search

Disclosure statement

The authors report that there are no competing interests to declare.

Notes

1 http://www.miit-eidc.org.cn/module/download/downfile.jsp?classid=0&filename=796c489e07af421aa43e9012e5147da1.pdf.

Additional information

Funding

This work is supported by research grants from the National Natural Science Foundation of China [72171105, 71801058], Humanity and Social Science Youth Foundation of the Ministry of Education of China [21YJC630133], Fundamental Research Funds for the Central Universities [21lzujbkyjh008], and the Liuzhou Science and Technology Project [2021CBA0103].