A Review of Evolutionary Multi-modal Multi-objective Optimization
Ryoji Tanabe, Hisao Ishibuchi

TL;DR
This paper reviews the evolution of multi-modal multi-objective optimization, highlighting its development since 2005, the challenges in surveying existing work, and clarifying open research issues in the field.
Contribution
It provides a comprehensive survey of studies in evolutionary multi-modal multi-objective optimization, including those not explicitly labeled as such, and identifies open research challenges.
Findings
Reviewed studies from 2005 onwards
Clarified terminology and scope of the field
Identified open issues and future directions
Abstract
Multi-modal multi-objective optimization aims to find all Pareto optimal solutions including overlapping solutions in the objective space. Multi-modal multi-objective optimization has been investigated in the evolutionary computation community since 2005. However, it is difficult to survey existing studies in this field because they have been independently conducted and do not explicitly use the term "multi-modal multi-objective optimization". To address this issue, this paper reviews existing studies of evolutionary multi-modal multi-objective optimization, including studies published under names that are different from "multi-modal multi-objective optimization". Our review also clarifies open issues in this research area.
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