结合非固定多段罚函数的约束优化进化算法  

Constrained Optimization Evolutionary Algorithm Combining Non-stationary Multi-stage Penalty Function

作　　者：邹木春[1] 

机构地区：[1]宜春学院数学与计算机学院,江西宜春336000

出　　处：《计算机工程》2012年第12期165-168,共4页Computer Engineering

摘　　要：利用非固定多段映射罚函数的约束条件,提出一种结合非固定多段罚函数的约束优化进化算法。该算法利用佳点集方法初始化种群,以保证其均匀分布在搜索空间中。在进化过程中,对种群进行单形交叉和多样性变异操作产生新的个体,增加种群的多样性。对6个经典Benchmark问题进行测试,实验结果表明,该算法能有效地处理不同的约束优化问题。Using non-stationary multi-stage assignment penalty function to deal with the constrained conditions,a modified constrained optimization evolutionary algorithm is proposed.In the process of evolution,in order to ensure the population evenly distributed in the search space,the individuals generation based on good point set method is introduced into the evolutionary algorithm initial step.The offspring population individuals are generated by simplex crossover and diversity mutation operator to maintain the diversity of population.Six classic Benchmark problems are tested.Experimental results show that the proposed algorithm is an effective way for constrained optimization problems.

关 键 词：约束优化问题 进化算法 非固定多段罚函数 单形交叉 变异 佳点集 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]