一种改进的非支配排序遗传算法

An Improved Evolutionary Algorithm for Multi-objective Optimization

  • 摘要: 为克服非支配排序遗传算法计算复杂度高,未采用精英策略,需要特别指定共享半径的缺点,提出了一种改进的非支配排序遗传算法.通过实验验证,该算法在几个给定的函数优化时都能取得比较好的结果.

     

    Abstract: Multi-objective evolutionary algorithms which use non-dominated sorting and sharing have been mainly criticized for the problems, (1) O(mN3) computational complexity (where m is the number of objectives and n is the population size), (2) non-elitism approach, and (3) the need for specifying a sharing parameter. This paper suggests a non-dominated sorting based the multi-objective evolutionary algorithm INSGA which alleviates all the above three difficulties. Simulation results on five difficult test problems show that the proposed INSGA is able to find much better spread of solutions in all problems compared to NSGA.

     

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