An Efficient Evolutionary Algorithm for Accurate Polygonal Approximatio

Abstract

This paper proposes an efficient evolutionary algorithm (EEA) with a novel orthogonal array crossover (OAX) for solving the accurate polygonal appraximation problem. Using the OAX, the chrom osomes of the children are formed from the best combinations of the beter genes from the parents rather than the conventional random combinations of the parents' genes. The choice of the better genes is derived by way of a systematic reasoning approach for evaluatin contributionof the individual gene based on the orthogonal arra. Genetic algorithm approach has been proposed and its performance is much better than that of several superior mehtods in obtaining accurate solutions of polygonal approximation problems. It is shown empirically that the proposed EEA outperforms the superior genetic algorithm proposed in litemture under the same cost condition in the quality of the best solution, average solution, variance of solutions, and the convergence speed, expecially in solving large polygonal approximation problems.