Finding knee solutions in multi-objective optimization using extended angle dominance approach

Abstract

The aim of this paper is to develop a knee-based multi-objective evolutionary algorithm (MOEA) which is a method to find optimal trade-off solutions among all available solutions. In multi-objective optimization, the knee regions represent implicitly preferred parts to the decision maker (DM). The proposed approach uses the extended angle dominance concept to guide the solution process towards knee regions. The extent of the obtained solutions can be controlled by the means of user-supplied density controller parameter. The approach is verified by two and three objective knee-based test problems. The results have shown that our approach is competitive to well-known knee-based MOEAs in convergence view point.