基于空间自适应收缩策略的混合遗传算法及其应用
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摘要
将简单遗传算法与单纯形法相杂合,设计了一种实数编码的混合遗传算法(HGA),用于求解无约束优化问题。算法采用了最优保留策略,同时在变异操作中采用了搜索空间的自适应收缩策略,以提高全局和局部搜索能力,加快收敛速度,避免退化。在求解约束优化问题时,利用罚函数处理约束条件,由HGA对增广目标函数寻优。HGA的有效性通过3个典型测试函数得到验证,并应用于拍合式继电器电磁系统的体积优化。
A real-coded hybrid genetic algorithm (HGA) was designed by hybridizing the simple genetic algorithm and simplex algorithm to solve unconstrained optimization problems. In order to avoid degeneration and to improve the global and local searching property and the convergence speed, the optimum maintaining strategy was adopted and the searching-space was shortened adaptively via mutation operator. When solving a constrained optimization problem, a set of penalty functions was used to process the constraints and HGA was used to optimize the generalized objective function. The validity of HGA in this work was verified by three typical functions. Further more, an application was introduced for the volume optimization of electromagnet system of clapper-type relay.
A real-coded hybrid genetic algorithm (HGA) was designed by hybridizing the simple genetic algorithm and simplex algorithm to solve unconstrained optimization problems. In order to avoid degeneration and to improve the global and local searching property and the convergence speed, the optimum maintaining strategy was adopted and the searching-space was shortened adaptively via mutation operator. When solving a constrained optimization problem, a set of penalty functions was used to process the constraints and HGA was used to optimize the generalized objective function. The validity of HGA in this work was verified by three typical functions. Further more, an application was introduced for the volume optimization of electromagnet system of clapper-type relay.
引文
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[13] 李玲玲.继电器产品设计及评价专家系统的构建方法研究[D].天津:河北工业大学,2004.
[2] 宗敬群.一类混合自适应遗传算法及性能分析[J].系统工程理论与实践,2001,21(4):14~18.
[3] 韩 炜,廖振鹏.一种全局优化算法:遗传算法——单纯形法[J].地震工程与工程振动,2001,21(2):6~12.
[4] BEVERIDGE J R,BALASUBRAMANIAM K,WHITLEY D.Matching Horizon Features Using a Messy Genetic Algorithm[J].Computer Methods in Applied Mechanics and Engineering,2000,186(2-4):499~516.
[5] YAN X F,CHEN D Z,HU S X.Chaos-Genetic Al-gorithms for Optimizing the Operating Conditions Based on RBF-PLS Model[J].Computers and Chemi-cal Engineering,2003,27(10):1393~1404.
[6] TSUTSUI S,FUJIMOTO Y,GHOSH A.A Forking Genetic Algorithms:Gas with Search Space Division Schemes[J].Evolutionary Computation,1997,5(1):61~80.
[7] KIM Y K,KITAE P,KO J.A Symbiotic Evolution-ary Algorithm for the Integration of Process Planning and Job Shop Scheduling[J].Computers and Opera-tions Research,2003,30(8):1151~1171.
[8] CUI Z H,ZENG J C.Studying of Nonlinear Genetic Algorithms[C]//Proceedings of the4th Word Con-gress on Intelligent Control and Automation.Shang-hai,China:Press of East China University of Science and Technology,2002:812~814.
[9] PEREIRA CL UDIO M N A,LAPA CELSO M F.Coarse-Grained Parallel Genetic Algorithm Applied to a Nuclear Reactor Core Design Optimization Problem[J].Annals of Nuclear Energy,2003,30(5):555~565.
[10] MUHAMMAD A,BARGIELA A,KING G.Fuzzy and Evolutionary Modeling of Nonlinear Control Sys-tems[J].Mathematical and Computer Modelling,2001,33(4-5):533~551.
[11] MASAO A,ICHIRO H.Development of Adaptive Real Range Genetic Algorithms[J].JSME Series-C,1998,41(4):969~977.
[12] 饶进军,包忠诩,黄菊花.一种高效综合的遗传算法[J].南昌大学学报(工科版),2002,24(1):1~4.
[13] 李玲玲.继电器产品设计及评价专家系统的构建方法研究[D].天津:河北工业大学,2004.
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