Multi-objective vehicle routing problem with time windows under uncertain conditions

Jiashuo Guo; Yuxin Liu

doi:10.1117/12.3014402

9 January 2024 Multi-objective vehicle routing problem with time windows under uncertain conditions

Jiashuo Guo, Yuxin Liu

Proceedings Volume 12969, International Conference on Algorithm, Imaging Processing, and Machine Vision (AIPMV 2023); 129692C (2024) https://doi.org/10.1117/12.3014402
Event: International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023), 2023, Qingdao, China

Abstract

In this paper, we research the multi-objective vehicle routing problem with time windows under uncertainty. For solving it efficiently, the robust multi-objective particle swarm optimization incorporates the simulated annealing algorithm is proposed. The new algorithm aims to improve the local search abilities of particles. Experimental results show that the proposed algorithm outperforms the traditional the robust multi-objective particle swarm optimization algorithm on the selected problem sets as the uncertain interference intensity increases.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jiashuo Guo and Yuxin Liu "Multi-objective vehicle routing problem with time windows under uncertain conditions", Proc. SPIE 12969, International Conference on Algorithm, Imaging Processing, and Machine Vision (AIPMV 2023), 129692C (9 January 2024); https://doi.org/10.1117/12.3014402

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