D-MAENS2: A Self-adaptive D-MAENS Algorithm with Better Decision Diversity

Qingquan Zhang1; Feng Wu2; Yang Tao1; Jiyuan Pei1; Jialin Liu1; Xin Yao1

10.1109/SSCI47803.2020.9308250

2020

2020 IEEE Symposium Series on Computational Intelligence (SSCI)

978-1-7281-2548-0

2020 IEEE Symposium Series on Computational Intelligence (SSCI)

2754-2761

2020-12-1

Canberra, ACT, Australia

The capacitated arc routing problem is a challenging combinatorial optimization problem with numerous real-world applications. In recent years, several multi-objective optimization algorithms have been applied to minimize both the total cost and makespan for capacitated arc routing problems, among which the decomposition-based memetic algorithm with extended neighborhood search has shown promising results. In this paper, we propose an improved decomposition-based memetic algorithm with extended neighborhood search, called D-MAENS2, which uses a novel method to construct a gene pool to measure and improve the diversity of solutions in decision variable space. Additionally, D-MAENS2 is capable of adapting online its hyper-parameters to various problem instances. Experimental studies show that our novel D-MAENS2 significantly outperforms D-MAENS on 81 benchmark instances and shows outstanding performance on instances of large size.

Capacitated arc routing problem local search memetic algorithms meta-heuristics multiobjective optimization

第一 ; 通讯

CPCI-S ; EI

20210409827846

Combinatorial optimization ; Intelligent computing ; Multiobjective optimization ; Network routing

Artificial Intelligence:723.4 ; Optimization Techniques:921.5

人工提交

1.Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen 518055, China
2.Northwestern Polytechnical University Xi’an, Shaanxi, 710129, China

Qingquan Zhang,Feng Wu,Yang Tao,et al. D-MAENS2: A Self-adaptive D-MAENS Algorithm with Better Decision Diversity[C],2020:2754-2761.