一种求解约束优化问题的进化算法及其工程应用

Evolutionary algorithm for constrained optimization problem and its engineering applications

提出一种改进的用于求解约束优化问题的进化算法。该算法利用混沌方法初始化个体以保证其均匀分布在搜索空间中。在进化过程中,将种群分为可行子种群和不可行子种群,分别采用不同的交叉和变异操作,以平衡算法的全局和局部搜索能力。标准测试问题的实验结果表明了改进算法的有效性。最后将改进算法应用到两个工程优化设计问题中,得到了满意的结果。

A modified evolutionary algorithm （MEA） is proposed to solve constrained optimization problems. Chaotic sequence method is introduced to construct the initialization population that is scat tered uniformly over the entirely search space in order to maintain the diversity. In the evolution process, our algorithm is based on individual feasibility; the population is divided into feasible subpopu- lation and infeasible subpopulation, which evolve with different crossover operator and different muta- tion operator, respectively. Numerical simulation results on four benchmark problems demonstrate the effectiveness and robustness of the proposed algorithm. Several engineering optimization problems are designed to test the MEA, and the results show that the MEA can solve different constrained optimiza- tion problems.