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

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

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The capacitated arc routing tokidoki hello kitty blind box 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 read more 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.