计算机科学 ›› 2010, Vol. 37 ›› Issue (2): 192-195.

• 人工智能 • 上一篇    下一篇

基于自适应算子的混合进化算法及其应用

游晓明,刘升,帅典勋   

  1. (上海工程技术大学电子电气工程学院 上海200065);(华东理工大学计算机科学与技术系 上海200237)
  • 出版日期:2018-12-01 发布日期:2018-12-01
  • 基金资助:
    本文受国家自然科学基金项目(资助号:60575040),上海市自然科学基金项目(资助号:09ZR1420800),大学生创新项目(资助号:cx0902006)资助。

Hybrid Evolutionary Algorithm Based on Adaptive Operator and its Application

YOU Xiao-ming,LIU Sheng,SHUAI Dian-xun   

  • Online:2018-12-01 Published:2018-12-01

摘要: 提出了一种求解多目标优化最短路径问题的混合进化算法。算法中依据小生境机制生成若干个实数编码染色体的子群,各子群分别利用自适应算子的局域搜索能力找出优化解。协同进化机制能更好地保证进化的方向性和种群的多样性,基于路径表示的染色体十进制编码方法以及染色体的交又和变异具有新颖性。该算法用于解决智能交通系统的公共交通线路换乘问题,实验结果表明了其优越性。还运用Markov随机过程理论证明了算法的收敛性。

关键词: 进化算法,自适应算子,十进制编码染色体,最短路径,小生境

Abstract: A novel hybrid evolutionary algorithm based on adaptive operator for solving multi-objective optimisation was proposed. By niche methods population is divided into subpopulations of real-coded chromosome automatically, each subpopulation can obtain optimal solution by self-adaptive mechanism. We introduced real-coded chromosome with innovalion to solve precision and efficiency problem of binary system; co-evolutionary strategy of niche can guarantee ctuite nicely the population diversity and the convergence speed. The algorithm is applied to urban public transportation system transfer, and experimental results show its superiority. The convergence of the algorithm is proved based on Markov chain in this paper.

Key words: Evolutionary algorithm, Sclf-adaptive operator, Real-coded chromosome, Shortest path, Niche

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