Improving Neighborhood Exploration Mechanism to Speed up PLS

Yuhao Kang, Jialong Shi, Jianyong Sun, Ye Fan

科研成果: 书/报告/会议事项章节会议稿件同行评审

1 引用 (Scopus)

摘要

As an extension of local search for multiobjective case, the basic version of Pareto Local Search (PLS) suffers from a poor anytime behavior. Researches have been carried out to overcome this drawback from different aspects. In this paper, we focus on the mechanism of neighborhood exploration in bi-objective Travelling Salesman Problems (bTSPs). Inspired by existing fast local search strategies for single objective TSP, we propose two speed-up strategies to help PLS quickly find promising neighboring solutions in bTSPs. In the experimental studies, we investigate the sensitivity of parameters and test the performance of several PLS variants with different combinations of the two strategies. The experimental results verify the effectiveness of the two strategies and their combination.

源语言英语
主期刊名GECCO 2023 - Proceedings of the 2023 Genetic and Evolutionary Computation Conference
出版商Association for Computing Machinery, Inc
688-694
页数7
ISBN(电子版)9798400701191
DOI
出版状态已出版 - 15 7月 2023
活动2023 Genetic and Evolutionary Computation Conference, GECCO 2023 - Lisbon, 葡萄牙
期限: 15 7月 202319 7月 2023

出版系列

姓名GECCO 2023 - Proceedings of the 2023 Genetic and Evolutionary Computation Conference

会议

会议2023 Genetic and Evolutionary Computation Conference, GECCO 2023
国家/地区葡萄牙
Lisbon
时期15/07/2319/07/23

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