Comparative performances of three GA based multi-objective algorithms for optimal design of laminate composites

摘要

In this paper, implementation details of three popular evolutionary multi-objective algorithms: Non-dominated sorting Genetic Algorithm (NSGA-II), Pareto Archived Evolutionary Strategy (PAES) and Strength Pareto Evolutionary Algorithm-H( SPEA-II), for solving combinatorial optimization problems associated with laminate composite structures are discussed. All these three multi-objective evolutionary algorithms are employed to solve a hybrid laminate composite plate problem subjected to both combinatorial as well as design constraints. Later set of performance metrics for evaluating multi-objective algorithms are used to investigate the comparative performance of the three evolutionary algorithms. The studies presented in this paper indicate that NSGA-II and PAES algorithms produces competitive Pareto fronts according to the applied convergence metric.