Multi-objective optimization using differential evolution: A survey of the state-of-the-art

Abstract

Differential Evolution is currently one of the most popular heuristics to solve single-objective optimization problems in continuous search spaces. Due to this success, its use has been extended to other types of problems, such as multi-objective optimization. In this chapter, we present a survey of algorithms based on differential evolution which have been used to solve multi-objective optimization problems. Their main features are described and, based precisely on them, we propose a taxonomy of approaches. Some theoretical work found in the specialized literature is also provided. To conclude, based on our findings, we suggest some topics that we consider to be promising paths for future research in this area. © 2008 Springer-Verlag Berlin Heidelberg.