Tutorial - Evolutionary Many-Objective Optimization

Hiroyuki Sato,The University of Electro-Communications,Japan; Hisao Ishibuchi, Southern University of Science and Technology, China ABSTRACT: Evolutionary multi-objective optimization (EMO) has been a very active research area in the field of evolutionary computation in the last two decades. In the EMO area, one of the hottest research topics is evolutionary many-objective optimization. The difference between multi-objective and many-objective optimization is simply the number of objectives. Multi-objective problems with four or more objectives are usually referred to as many-objective problems. The increase in the number of objectives significantly makes multi-objective problems difficult. The goal of the tutorial is to clearly explain difficulties of evolutionary many-objective optimization, approaches to the handling of those difficulties, and promising future research directions.