孙超利,谭瑛,潘正祥,曾建潮

• 1:太原科技大学计算机科学与技术学院
• 2:高雄应用科技大学电子学院

摘要(Abstract)：

约束保持法是目前求解约束问题时处理约束的主要方法之一,该方法的思想是确保进化过程中所有粒子始终在可行域范围内。本文借鉴复合形法的思想,提出一种求解约束优化问题的新方法。当粒子超出可行域范围时,通过反射、扩张、收缩等操作,为粒子重新产生一个可行位置。通过对标准函数仿真实验表明,该算法实现原理简单,而且能得到较优的解。

关键词(KeyWords)： 微粒群;约束保持法;约束优化问题;复合形法

Abstract:

Keywords:

基金项目(Foundation): 山西自然科学基金(2008011027-2);山西自然科学基金(20081030);; 国家自然科学基金(60674104)

作者(Author): 孙超利,谭瑛,潘正祥,曾建潮

参考文献(References)：

• [1]王俊艳,曾建潮.应用微粒群算法提取分类规则[J].太原科技大学学报,2008,29(4):284-287.
• [2]尉小环,高慧敏,李峰.微粒群算法在软件测试数据生成中的引用[J].太原科技大学学报,2009,30(4):294-296.
• [3]PARSOPOULOS K E VRAHATIS MN.Particle swarm optimization method for constrained optimization problems[C]//Proceed-ings of the second Euro-International Symposium on Computational Intelligence Intelligent Technologie,2002:214-220.
• [4]KAI SEDLACZEK,PETER EBERHARD.Constrained Particle Swarm Optimization of Mechanical Systems[C]//6th World Con-gresses of Structural and Multidisciplinary Optimization,2005:1-10.
• [5]PULIDO G T,COELLO C A C.A constraint-handling mechanism for particle swarm optimization[C]//Congress on EvolutionaryComputation,2004:1396-1403.
• [6]SUN C,ZENG J,PAN J.An Improved Particle Swarm Optimization with Feasibility-Based Rules for Constrained OptimizationProblems[C]//22nd International Conference on Industrial,Engineering and Other Applications of Applied Intelligent Systems,2009:202-211.
• [7]HUX,EBERHARTR.Solving Constrained Nonlinear Optimization Problems with Particle Swarm Optimization[C]//Proceedingsof the 6th World Multiconference on Systemics,Cybernetics and Informatics,Orlando,USA,2002:884-889.
• [8]SUNC ZENG J,PANJ.An NewVector Particle Swarm Optimization for Constrained Optimization Problems[C]//Proceedings ofthe 2009 International Joint Conference on Computational Sciences and Optimization,2009:485-488.
• [9]刘惟信.机械最优化设计[M].北京:清华大学出版社,1994.
• [10]DEB K.An efficient constraint handing method for genetic algorithms[J].Computer Methods in Applied Mechanics and Engi-neering(S0045-7825),2000,186(2):311-338.
• [11]KENNEDY J,EBERHARTR.Particle swarm optimization[C]//Proc IEEE Int Conf on Neural Networks,Perth,1995:1942-1948.
• [12]EBERHART R,KENNEDY J.A new optimizer using particle swarm theory[C]//Proc 6th Int Symposiumon Micro Machineand Human Science,Nagoya,1995:39-43.
• [13]SHI YUHUI,EBERHARTR.A modified particle swarm optimizer[C]//Proc IEEE Int Conf on Evolutionary Computation.AN-CHORAGE,1998:69-73.
• [14]RUNARSSON TP,YAO X.Stochastic ranking for constrained evolutionary optimization[J].IEEE Transactions on EvolutionaryComputation,2000,4(3):284-294.
• [15]KOZIEL S,MICHALEWICZ Z.Evolutionary algorithm,homomorphous mapping and constrained parameter optimization[J].Ev-olutionary Computation,1999,7(1):19-44.