A Hybrid Brain Storm Optimization Algorithm for Dynamic Vehicle Routing Problem

Liu，Mingde; Shen，Yang; Shi，Yuhui

10.1007/978-3-030-53956-6_23

2020

0302-9743

1611-3349

LECT NOTES ARTIF INT

12145 LNCS

251-258

The Dynamic Vehicle Routing Problem (DVRP) has many real-world applications and practical values. The objective of DVRP is to find the optimal routes for a fleet of vehicles to service the given customer requests, without violating the vehicle capacity constraint. In this paper, a hybrid algorithm is proposed for solving the DVRP with the objective to minimize the total distance of the vehicles. The Brain Storm Optimization in objective space (BSO-OS) is applied to guide the choice of different strategies for the periodic reoptimization of routes. In the BSO-OS procedure, Adaptive Large Neighborhood Search (ALNS) and Ant Colony System (ACS) are used to generate new solutions. The experiments on the DVRP benchmark and comparative studies are conducted, from which 12 out of 21 new best solutions are obtained by the proposed algorithm, and the other nine solutions are also very competitive. The experimental results show that the proposed algorithm is very effective and competitive.

Adaptive Large Neighborhood Search Ant colony system Brain storm optimization in objective space Dynamic vehicle routing problem

第一 ; 通讯

英语

EI

20203109001571

Ant colony optimization ; Swarm intelligence ; Vehicles ; Fleet operations ; Routing algorithms ; Vehicle routing

Precipitation:443.3 ; Computer Software, Data Handling and Applications:723 ; Artificial Intelligence:723.4 ; Optimization Techniques:921.5

2-s2.0-85088742837

Scopus

Department of Computer Science and Engineering,Southern University of Science and Technology,Shenzhen,518055,China

Liu，Mingde,Shen，Yang,Shi，Yuhui. A Hybrid Brain Storm Optimization Algorithm for Dynamic Vehicle Routing Problem[C],2020:251-258.