Infeasible Elitists and Stochastic Ranking Selection in Constrained Evolutionary Multi-objective Optimization

Abstract

To handle the constrained multi-objective evolutionary optimization problems, the authors firstly analyze Deb’s constrained-domination principle (DCDP) and point out that it more likely stick into local optimum on these problems with two or more disconnected feasible regions. Secondly, to handle constraints in multi-objective optimization problems (MOPs), a… (More)
DOI: 10.1007/11903697_43

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