计算机与现代化 ›› 2010, Vol. 1 ›› Issue (10): 12-15,1.doi: 10.3969/j.issn.1006-2475.2010.10.004

• 人工智能 • 上一篇    下一篇

多亲交叉遗传算法及其在旅行商问题中的应用

张民强   

  1. 淮海工学院计算机工程学院,江苏 连云港 222005
  • 收稿日期:2010-06-24 修回日期:1900-01-01 出版日期:2010-10-21 发布日期:2010-10-21

Multi-parent Crossover Genetic Algorithm and Its Application in Traveling Salesman Problem

ZHANG Min-qiang   

  1. School of Computer Engineering, Huaihai Institute of Technology, Lianyungang 222005, China
  • Received:2010-06-24 Revised:1900-01-01 Online:2010-10-21 Published:2010-10-21

摘要: 针对传统遗传算法早熟收敛的缺点,提出多亲交叉遗传算法。与贪婪交叉算子相比,该交叉算子能够有效保留父代优质个体特征,维持群体多样性,同时能够很好地平衡深度搜索与广度搜索。基于旅行商问题的仿真测试表明了多亲交叉遗传算法的有效性。

关键词: 多亲交叉, 遗传算法, 多样性, 旅行商问题

Abstract: In order to overcome premature convergence of traditional genetic algorithm (TGA), a multi-parent crossover GA (MPCGA) is proposed. Compared with greedy crossover, the proposed crossover can not only preserve the useful information of parent, but also maintain the diversity of population. In addition, the novel algorithm can also balance the trade-off between the exploitation and the exploration. Simulation results on traveling salesman problem (TSP) show the effectiveness and robustness of the novel multi-parent crossover GA.

Key words: multi-parent crossover, GA, diversity, traveling salesman problem (TSP)

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