Improved Memetic Algorithm for Multi-depot Multi-objective Capacitated Arc Routing Problem

• Main Authors: Wan Jie, Chen Xinghan, Li Ruichang
• Format: Article
• Language: English
• Published: EDP Sciences 2020-01-01
• Series: MATEC Web of Conferences
• Online Access: https://www.matec-conferences.org/articles/matecconf/pdf/2020/04/matecconf_ictte2019_01002.pdf

The capacitated arc routing problem (CARP) is a challenging vehicle routing problem with numerous real-world applications. In this paper, an extended version of CARP, the multi-depot multi-objective capacitated arc routing problem (MDMOCARP) is proposed to tackle practical requirements. Firstly, the critical edge decision mechanism and the critical edge random allocation mechanism are proposed to optimize edges between depots. Secondly, a novel adaptive probability of local search with fitness is proposed to improve the Decomposition-Based Memetic Algorithm for Multi-Objective CARP (D-MAENS). Compared with the D-MAENS algorithm, experimental results on MD-CARP instances show that the improved memetic algorithm (IMA) has performed significantly better than D-MAENS on convergence and diversity in the metric IGD and the metric HV.