A Survey on Multimodal Multiobjective Optimization Algorithm

Jiaying Wang; Yinxing Chen; Weijie Wu

doi:10.54097/mnmgr098

Authors

Jiaying Wang
Yinxing Chen
Weijie Wu

DOI:

https://doi.org/10.54097/mnmgr098

Keywords:

Multimodal Multi-objective, Optimization Algorithms, Benchmark Problems

Abstract

With the diversification of industrial production and daily life needs, traditional single modal multi-objective optimization algorithms are no longer able to meet complex decision-making requirements. Multimodal multi-objective optimization algorithms (MMOPAs) provide decision- makers with more options by offering multiple feasible Pareto optimal solution sets. This article provides a detailed analysis of the research background and related concepts of multimodal multi-objective optimization algorithms. It analyzes the current development status of multimodal multi-objective optimization algorithms, introduces commonly used benchmark problems and evaluation indicators, and finally explaines future research directions.

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