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求解双层规划问题的层次混沌量子遗传算法
Hierarchical Chaotic Quantum-inspired Genetic Algorithm for Solving Bi-level programming problem
摘要点击 3378  全文点击 0  投稿时间:2011-07-12  修订日期:2012-01-05
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中文关键词  层次混沌量子遗传算法;双层规划;约束优化
英文关键词  Hierarchical Chaotic Quantum-inspired Genetic Algorithm;Bilevel programming ; Constrained optimization
基金项目  国家自然科学基金项目(面上项目,重点项目,重大项目)
作者单位E-mail
李昌兵 重庆邮电大学 lcbss@126.com 
中文摘要
      基于量子位的混沌特性和相干特性,提出针对一般双层规划问题的层次混沌量子遗传算法(HCQGA)。结合进化博弈及多目标优化非支配排序的思想,通过两个混沌量子遗传算法的交互迭代来模拟决策者之间的博弈寻优过程,从而获得使各方利益最大化的双层规划问题的最优解。算法测试结果表明,该算法不仅可以获得pareto 最优解集合,而且还可以克服现有双层规划算法在解决大规模问题时存在的算法复杂度及计算效率问题。
英文摘要
      This paper proposed a Hierarchical chaotic quantum-inspired genetic algorithm to solve general bilevel programming problem based on the chaotic and coherent characters of Q-bit. In order to maximize the interests of all parties, by the interaction of two CQGA iterations to simulate the interaction between policy-makers during the game searching , it can obtain the optimal solution of bilevel programming problems combing the idea of evolution game and multi-objective optimization non-dominated sort. Simulation shows that the proposed HCQGA not only obtained Pareto optimal solution set,but also avoid the shortcomming of the complexity and efficiency issues of the existing bilevel programming algorithm to solve large scale problems.
相关附件:   李昌兵20110712001修改稿Latex源文件  李昌兵20110712001稿件修改说明  李昌兵稿件20110712001Latex源文件  李昌兵20110712001修改稿LaTeX源文件  李昌兵20110712001修改稿LaTeX源文件
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