Finite persisting sphere Genetic Algorithm in solving multiobjectives problem

K. Kamil, Chong Kok Hen, T. S. Kiong, Yeap Kim Ho
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引用次数: 2

Abstract

This paper analyzes the performance of Genetic Algorithm using a new concept, namely Finite Persisting Sphere Genetic Algorithm (FPSGA). This algorithm shows the unique method in achieving fast convergence and great diversity for the multiobjective problem. These special characteristics of FPSGA are very useful in order to improve Genetic Algorithm (GA) performance to have great individuals mingling in the area of solution. Besides can help a system to solve a GA problem in a short duration, it can also prevent the solutions from trapped in the local optimum.
求解多目标问题的有限持续球遗传算法
本文利用有限持续球遗传算法(FPSGA)这一新概念分析了遗传算法的性能。该算法在实现多目标问题的快速收敛和大多样性方面具有独特的方法。FPSGA的这些特性对于提高遗传算法(GA)的性能,使其在解区域有大量的个体混合是非常有用的。它不仅可以帮助系统在短时间内解决遗传算法问题,还可以防止解陷入局部最优。
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