A Preference-Based Multiobjective Evolutioary Algorithm for Finding Knee Solutions
Sufian Sudeng, Naruemon Wattanapongsakorn · Applied Mechanics and Materials · 2015
The aim of this paper is to develop a knee-based Multi-Objective Evolutionary Algorithm (MOEA) which is a method to find optimal solutions focusing on knee regions. The knee solutions are very interesting to the decision maker (DM) when he/she does not have an explicit preference. The proposed approach uses the extended angle-based dominance concept to guide the search towards knee regions. The extent of the obtained solutions can be controlled by the means of user-supplied density controller parameter. The approach is demonstrated with 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.