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计算机工程

• 人工智能及识别技术 • 上一篇    下一篇

多交叉混沌选择反向小生境遗传算法

韩 维a,史玮韦b,司维超b   

  1. (海军航空工程学院 a. 一系;b. 研究生管理大队,山东 烟台 264001)
  • 收稿日期:2013-05-02 出版日期:2014-06-15 发布日期:2014-06-13
  • 作者简介:韩 维(1970-),男,教授、博士,主研方向:智能优化算法;史玮韦、司维超,博士。
  • 基金资助:
    国家自然科学基金资助项目(60902054);中国博士后科学基金资助项目(20090460114, 201003758)。

Opposition Niche Genetic Algorithm of Multi-crossover Chaotic Selection

HAN Wei a, SHI Wei-wei b, SI Wei-chao b   

  1. (a. No.1 Department; b. Graduate Student’s Brigade, Naval Aeronautical and Astronautical University, Yantai 264001, China)
  • Received:2013-05-02 Online:2014-06-15 Published:2014-06-13

摘要: 为提高小生境遗传算法的全局以及局部搜索能力,提出一种多交叉混沌选择反向小生境遗传算法。利用分段线性混沌映射函数生成一组混沌数序列,在每次进行交叉操作前,依据序列中对应元素的数值大小选择不同的交叉算子进行操作,通过小生境遗传算法产生较优的子代种群。针对子代种群,应用反向搜索策略获得反向种群,在子代种群和反向种群中进行精英选择得到最终新种群,以进一步加强算法的局部寻优能力。仿真实验结果表明,该算法在最优解及均值方面好于小生境遗传算法,从而证明其可行性和优越性。

关键词: 小生境遗传, 多交叉, 分段线性混沌映射, 反向搜索, 优化, 精英选择

Abstract: An opposition niche genetic algorithm of multi-crossover chaotic selection is proposed to enhance global and local searching ability of the niche genetic algorithm. Piecewise linear chaotic map is brought to generate a chaotic sequence. Each element of this sequence is picked up before every crossover operation and corresponding crossover operator is chose according to the range of the element. Through the rest operation of niche genetic algorithm, excellent offspring population is obtained. Finally, opposition searching strategy is adopted to produce opposition offspring population. The ultimate offspring population choose better individuals from two populations to improve the local searching. Experimental results show the proposed algorithm is better than the other niche genetic algorithms in best solution and mean value. It shows that the algorithm is feasible and effective.

Key words: niche genetic, multi-crossover, piecewise linear chaotic map, opposition searching, optimization, elitist selection

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