一种求解约束优化问题的差分进化算法
首发时间:2010-01-08
摘要:基于差分进化算法的相关理论以及随机排序约束处理方法,本文提出了一种新的基于差分进化算法来解决约束优化问题。该算法对种群的进化采用了随机保留次优解的策略,有效的提高了种群多样性。对13个标准测试问题的测试结果表明,与动态惩罚函数的进化算法、人工免疫响应约束进化策略、可行性规则的差分进化算法以及采用随机排序的进化策略相比,新算法在收敛速度和求解精度上均具有一定的优势。
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A Differential Evolution Algorithm for Constrained Optimization Problem
Abstract:Based on differential evolution and stochastic ranking strategy, a differential evolution algorithm for constrained optimization problem is proposed in this paper. The proposed algorithm reserves sub-optimal solutions in the process of population evolution, which effectively enhances the diversity of the population. The experiment results on 13 well-known benchmark problems show that the proposed algorithm is capable of improving the search performance significantly in convergent speed and precision with respect to four techniques representative of the state-of -the-art in constrained optimization such as Evolutionary Algorithm based on Homomorphous Maps, Artificial Immune Response Constrained Evolutionary Strategy, and Constraint Handling Differential Evolution, and Evolutionary Strategies based on Stochastic Ranking.
Keywords: Differential Evolution Algorithm Constrained Optimization Stochastic Ranking
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