A Multi-Objective Evolutionary Algorithm and Its Convergence
Zhou Yu · Chinese Journal of Computers · 2004
Evolutionary algorithms are especially suited for multi-objective optimization problems. Many evolutionary algorithms have been successfully applied to various multi-objective optimization problems, however, theoretical results on multi-objective evolutionary algorithms are scarce. This paper analyzes the convergence properties of the MOEAs. It proposes a simple and pragmatic MOEA model based on grids. The convergence of MOEAs is defined and the general conditions of convergence are provided. It also shows that the proposed (μ+1)-MOEA strongly converges to Pareto optimal set with probability one under suitable condition. Numerical results illustrate that this algorithm is feasible and effective.