A Robust Evolutionary Algorithm for Constrained Multi-Objective Optimization Problems

In this paper, a new partial order relation is defined by combining constrained conditions and the objective functions, and a definition of constrained domination between two solutions is suggested, which is an extension to the definition of domination The consistency between Pareto optimal set obtained by means of the new definition and the Pareto optimal set satisfying the constrained conditions has been proved So when the individuals are evaluated or ranked, it isn’t needed to care about whether the individuals are feasible, therefore implementing a penalty parameterless constraint handling approach By using the theory of finite Markov chain, the convergence properties of this algorithm are proved Several benchmark MO optimization problems are taken to test this algorithm The numerical experiments show that the proposed approach provides good performance in terms of convergence and diversity of solutions