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最优化问题全局寻优的混合遗传算法
引用本文:王登刚,刘迎曦,李守巨.最优化问题全局寻优的混合遗传算法[J].力学学报,2002,34(3).
作者姓名:王登刚  刘迎曦  李守巨
作者单位:1. 同济大学建筑工程系,上海,200092
2. 大连理工大学工程力学系,大连,116024
基金项目:国家自然科学基金(10072014)资助项目.
摘    要:把BFGS方法作为一个与选择、交叉和变异平行的算子,嵌入到浮点编码遗传算法中,得到一种基于BFGS方法和浮点编码遗传算法的混合计算智能算法.该方法兼顾了遗传算法和BFGS方法两者的长处,既有较快的收敛速度,又能以非常大的概率求得最优化问题全局解.数值结果表明,混合方法是求解优化问题的一种有潜力的智能算法.

关 键 词:全局最优  混合算法  遗传算法  BFGS方法  非线性规划

HYBRID GENETIC ALGORITHMS OF GLOBAL OPTIMUM FOR OPTIMIZATION PROBLEMS
Wang Denggang.HYBRID GENETIC ALGORITHMS OF GLOBAL OPTIMUM FOR OPTIMIZATION PROBLEMS[J].chinese journal of theoretical and applied mechanics,2002,34(3).
Authors:Wang Denggang
Institution:Wang DenggangDepartment of Building Engineering,Tongji University,Shanghai 200092,ChinaLiu Yingxi Li ShoujuDepartment of Engineering Mechanics,Dalian University of Technology,Dalian 116024,China
Abstract:Based on the BFGS method and real-code genetic algorithms, a hybrid computa-tional intellective algorithm has been established by setting BFGS method in real-code geneticalgorithms. In the given hybrid genetic algorithm, the BFGS method is taken as a geneticoperator which parallels to the select, crossover and mutation operators. The hybrid algorithmhas paid attention to both the advantages of BFGS method and genetic algorithms. It not onlyhas a rather high convergence speed, but also can locate the global optimum with a rather largeprobability. Numerical results show that the present algorithm is a promising approach for solvingglobal optimization problems.
Keywords:global optimum  hybrid algorithms  genetic algorithms  BFGS method  nonlinearprogramming problems
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