EMOCA: An Evolutionary Multi-Objective Crowding Algorithm
R. Ganesh Rajagopalan, Chilukuri Krishna Mohan, K. Mehrotra, Pramod K. Varshney · Journal of Intelligent Systems · 2008
A .new evolutionary algorithm is proposed for solving multi-objective optimization problems, focusing on the issue of developing a diverse population of non-dominated solutions.The key new approach in this algorithm is to use a diversity-emphasizing probabilistic approach in determining whether an off-spring individual is considered in the replacement selection phase, along with the use of a non-domination ranking scheme.This evolutionary multi-objective crowding algorithm (EMOCA) is evaluated using nine benchmark multi-objective optimization problems and shown to produce nondominated solutions with significant diversity, outperforming three state-ofthe-art multi-objective evolutionary algorithms on most ofthe test problems.