On the real world applications of many-objective evolutionary algorithms

Abstract

Recently, many-objective evolutionary algorithms have been studied by many researchers. Most of research works were concentrated on developing new methods that can deal with the high number of objective functions of such complex problems. Proposing new scalable benchmarks and valid performance metrics are another two commonly discussed domains in many-objective optimization problems. Most of proposed algorithms have been used to solve different real-world problems from several domains and applications. There are many research papers were published to review and compare the performance of current many-objective evolutionary algorithms. On the other hand there is no work that presented to highlight and review the usage of such algorithms in real problems and applications. Therefore there is an increasing significance for analyzing and reviewing of the complex real world problems that solved using many-objective optimization evolutionary algorithm. In this paper, we review the recently research work that have been done in the domain of solving complex real-world problems using many objective evolutionary algorithms. In addition, the most important issues of metrics, benchmarks and algorithms will be discussed briefly.