Abstract
In this article, a new algorithm for solving multi-objective optimization problems is proposed by extending the single objective scatter search template to deal with multiple objectives. The features like Pareto dominance, density estimation, and an external archive to store the nondominated solutions are added. The traditional solution combination of scatter search template is however replaced with two-point crossover operator being used in evolutionary algorithms in order to improve the convergence characteristics of the proposed scatter search algorithm. The resulting hybrid scatter search algorithm is employed to solve stacking sequence optimization of hybrid fiber-reinforced composite plate, cylindrical shell, and pressure vessel. Performance metrics are used to demonstrate the effectiveness of the proposed algorithm over other popular evolutionary algorithms like NSAGA-II, PAES, Micro-GA, and MOPSO.
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