>> 自然科学版期刊 >> 2018年04期 >> 正文
遗传禁忌搜索算法收敛性和时间复杂度分析
供稿: 牟乃夏;徐玉静;李洁;张灵先 时间: 2018-07-18 次数:

作者:牟乃夏徐玉静李洁张灵先

作者单位:‍山东科技大学测绘科学与工程学院中国科学院地理科学与资源研究所资源与环境信息系统国家重点实验室

摘要:遗传禁忌搜索算法多用于车辆路径优化、旅行商问题等,试验证明:融合遗传算法与禁忌搜索算法的混合算法相比单一算法的性能有较大提升,但缺少理论证明。本文阐述了遗传禁忌搜索算法的混合策略,从理论上对该算法的收敛性进行了证明,对时间复杂度进行了分析。应用马尔科夫链模型证明了遗传禁忌搜索算法是以概率1收敛到全局最优解的,并应用求解随机算法时间复杂度的方法,即求解算法的期望收敛时间,估算了该算法的时间复杂度,结果证明该算法的时间复杂度与所得解的多样性、问题规模以及遗传算法的种群数量有关。

基金:国家自然科学基金资助项目(41771476);山东省自然科学基金资助项目(ZR2016DM02);

关键词:遗传算法;禁忌搜索算法;收敛性;时间复杂度;马尔科夫链模型;

Abstract:The hybrid of genetic algorithm and tabu search algorithm has greatly improved performances relative to one single algorithm. It has been widely used in vehicle route optimization and travel planning, etc. In this paper, a hybrid strategy of genetic tabu search algorithm was introduced and its convergence was theoretical proved. The time complexity of the algorithm was analyzed as well. By using Markov chain model, the algorithm of genetic tabu search was proved to have the global optimal solution with converge of probability 1. Meanwhile, its time complexity was calculated by a stochastic algorithm. Based on the above methods, the time complexity of the algorithm was obtained, which was proved to be highly related to the diversity of the solution, the problem scale and the population of the genetic algorithm.

DOI:10.16186/j.cnki.1673-9787.2018.04.18

分类号:TP18

最近更新