动态优化问题的改进微分进化

2012 Second International Conference on Intelligent System Design and Engineering Application Pub Date : 2012-01-06 DOI:10.1109/ISDEA.2012.647

Jiang Liqiang, Qiang Hongfu

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引用次数: 0

摘要

针对动态优化问题，提出了改进差分进化算法(MDE)。新算法将种群划分为两个子集，一个主子集和一个辅助子集。主子种群保持不变并局部搜索。辅助子种群随机重新初始化，并进行全局搜索。结果表明，该方法能够快速准确地跟踪变化的极值，能够有效地求解动态优化问题。

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Modified Differential Evolution for Dynamic Optimization Problems

Modified differential evolution algorithm (MDE) is proposed for dynamic optimization problems. The new algorithm divides the population into two, a main subpopulation and an assistant one. The main subpopulation keeps invariant and searches locally. The assistant subpopulatioin is re-initialized at random and searches globally. The results show that MDE can track the changing extreme promptly and accurately and is capable of efficiently solving dynamic optmization problems.

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2012 Second International Conference on Intelligent System Design and Engineering Application

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