Improved NSGA-II algorithm for solving multimodal multi-object path planning problem

Xiaotian Liang; Juan Jing; Kai Zhang

doi:10.1117/12.2639191

17 May 2022 Improved NSGA-II algorithm for solving multimodal multi-object path planning problem

Xiaotian Liang, Juan Jing, Kai Zhang

Proceedings Volume 12259, 2nd International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2022); 122595N (2022) https://doi.org/10.1117/12.2639191
Event: 2nd International Conference on Applied Mathematics, Modelling, and Intelligent Computing, 2022, Kunming, China

Abstract

This paper proposed an improved NSGA-II algorithm for solving multimodal multi-objective path planning problems. The proposed algorithm can find not only well-converged and well-distributed non-dominated optimal solutions, but also multiple equivalent shortest paths in the decision space. First, non-dominated sorting is adopted to select the wellconverged solutions. Second, the path similarity indicator is designed to maintain the diversity of the shortest paths. Finally, the performance of the proposed algorithm is evaluated on CEC 2021 competition MMOPP test set. The comparison results show the proposed algorithm has a competing performance than chosen state-of-the-art MMOEAs.

Citation Download Citation

Xiaotian Liang, Juan Jing, and Kai Zhang "Improved NSGA-II algorithm for solving multimodal multi-object path planning problem", Proc. SPIE 12259, 2nd International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2022), 122595N (17 May 2022); https://doi.org/10.1117/12.2639191

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