Research Progress and Challenges of Multimodal Multiobjective Evolutionary Algorithms for Global and Local Optimal Solutions

To reveal the recent research advances of multimodal multiobjective optimization evolutionary algorithms for global and local optimal solutions, first, the multimodal multiobjective optimization problem (MMOP) with global and local optimal solution sets is introduced and its related definitions and characteristics are provided. Second, a systematic category is presented according to the existing algorithms, and the technical characteristics of the methods are analyzed. Third, the test function sets with global and local optimal solution sets are introduced, and the common evaluation indicators are discussed. Finally, by analyzing the challenges, the future research directions of this field are identified.