一种融入小生境技术的遗传禁忌算法

针对遗传算法在全局优化问题中容易出现早熟和收敛速度慢,禁忌搜索强烈依赖于初始解等问题,根据遗传算法和禁忌搜索算法自身的特点,分析两者的优势和不足,提出了一种融入小生境技术的遗传禁忌算法.该算法采用融入了小生境技术的遗传算法作全局搜索,用禁忌搜索算法作局部搜索,可以加快收敛速度,同时可以抑制早熟现象,避免过早收敛到局部最优.分析和实验结果表明,该算法能很好地抑制早熟收敛,同时在计算速度和计算结果方面都有改进,是一种快速有效的优化算法.

A Hybrid Strategy Based on Genetic Algorithm and Tabu Search Importing Niches

Genetic algorithm and Tabu search algorithm are powerful tools to solve complicated large-scale optimization problems. To deal with the prematurity and low convergence speed when the genetic algorithm are used for global optimization and Tabu search depends strongly on its initial solution, a hybrid optimization algorithm was introduced through comprehensive contrast and comparison between the above two algorithms to improve the local search ability of Genetic algorithm. In this algorithm, Tabu search algorithm was used for local search and genetic algorithm was used for global search in order to speed up convergence for satisfactory results. Meanwhile, niche was imported to control prematurity and to avoid converging to local optimum. The test results show that both calculating speed and output are improved, so it is a fast and effective algorithm.