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

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...

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Bibliographic Details
Published inMATEC Web of Conferences Vol. 308; p. 1002
Main Authors Wan, Jie, Chen, Xinghan, Li, Ruichang
Format Journal Article Conference Proceeding
LanguageEnglish
Published Les Ulis EDP Sciences 2020
Subjects
Algorithms
Carp
Route planning
Vehicle routing
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Summary: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.
ISSN:2261-236X
2274-7214
2261-236X
DOI:10.1051/matecconf/202030801002