利用遗传算法搜索多个极值点

SEARCHING MULTI-MAXIMUM POINTS USING GENETIC ALGORITHMS

分析了遗传多峰搜索领域内现有方法的不足 .对传统的遗传算法引入了梯度算子和聚类算子 ,将近似导数平方和的倒数作为评价函数 ,并定义了罚项 .用改进后的遗传算法搜索多峰 .实测结果表明 ,该算法搜索速度明显加快 ,精度有很大提高 .对等高等距。

This paper analysis the shortage of the existing methods of searching multi maximum GA. Basing on traditional genetic algorithms, it use GA to search multi maximum by introducing gradient calculator and merging calculator and using the inverse of the sum of square of differential coefficient as fitness function and defining the punish function to distinct other situation. The test results contrast with “simple subpopulation schemes” show that the SMMGA is efficient on all types function and its convergence speed is quicker and its convergence precision is higher than other method.