自适应拟蒙特卡罗多极值优化方法（英文）

Adaptive Quasi-Monte Carlo Method for Multiple-Extrema Optimization

中文关键词  全局优化  不可微函数  拟蒙特卡罗方法  自适应搜索技术  子群体

英文关键词  global optimization  nondifferentable function  quasi-Monte Carlo methods  adaptive random search  sub-population

中文摘要

      拟蒙特卡罗搜索方法能用来有效地解决不可微优化问题. 借用遗传算法中种群的概念, 介绍了一种解全局优化的拟蒙特卡罗自适应搜索算法. 由于应用了自适应搜索技术, 局部搜索能够快速找到局部极值. 同时, 拟随机序列的低偏差性保证了函数定义域能够被均匀地搜索, 为找到多个局部极值包括全局极值提供了保证.

英文摘要

      Quasi-Monte Carlo random search is useful in nondifferentiable optimization. By borrowing the ideas of population from genetic algorithms, we introduce an adaptive random search in quasi-Monte Carlo method(AQMC) for global optimization. The adaptive search technique enables local search to head for local extrema quickly. The low discrepancy of quasi-random sequence ensures that the function field be searched evenly and various local extrema including global extremum be found.