An improved particle swarm optimization for carton heterogeneous vehicle routing problem with a collection depot

作者：Yao, Baozhen; Yu, Bin^*; Hu, Ping; Gao, Junjie; Zhang, Mingheng^*

来源：Annals of Operations Research, 2016, 242(2): 303-320.

DOI：10.1007/s10479-015-1792-x

• Carton
• Heterogeneous vehicle routing problem with a collection depot
• Particle swarm optimization
• Local search
• Self-adaptive inertia weight

In this paper, a carton heterogeneous vehicle routing problem with a collection depot is presented, which can collaboratively pick the cartons from several carton factories to a collection depot and then from the depot to serve their corresponding customers by using of heterogeneous fleet. Since the carton heterogeneous vehicle routing problem with a collection depot is a very complex problem, particle swarm optimization (PSO) is used to solve the problem in this paper. To improve the performance of the PSO, a self-adaptive inertia weight and a local search strategy are used. At last, the model and the algorithm are illustrated with two test examples. The results show that the proposed PSO is an effective method to solve the multi-depot vehicle routing problem, and the carton heterogeneous vehicle routing problem with a collection depot. Moreover, the proposed model is feasible with a saving of about 28 % in total delivery cost and could obviously reduce the required number of vehicles when comparing to the actual instance.

• 出版日期2016-7
• 单位大连海事大学; 大连理工大学