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Mixed Mutation Strategy Embedded Differential Evolution

机译:混合变异策略嵌入式差分进化。

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Differential evolution (DE) is a powerful yet simple evolutionary algorithm for optimizing real valued optimization problems. Traditional investigations with differential evolution have used a single mutation operator. Using a variety of mutation operators that can be integrated during evolution could hold the potential to generate a better solution with less computational effort. In view of this, in this paper a mixed mutation strategy which uses the concept of evolutionary game theory is proposed to integrate basic differential evolution mutation and quadratic interpolation to generate a new solution. Throughout of this paper we refer this new algorithm as, differential evolution with mixed mutation strategy (MSDE). The performance of proposed algorithm is investigated and compared with basic differential evolution. The experiments conducted shows that proposed algorithm outperform the basic DE algorithm in all the benchmark problems.
机译:差分进化(DE)是一种功能强大而又简单的进化算法,用于优化实值优化问题。具有差异进化的传统研究使用单个突变算子。使用可以在进化过程中集成的各种变异算子,可以节省计算量,从而产生更好的解决方案。有鉴于此,本文提出了一种利用进化博弈论概念的混合变异策略,将基本的差分进化变异与二次插值相结合,从而产生了新的解决方案。在本文中,我们将这种新算法称为带有混合突变策略(MSDE)的差分进化。对所提算法的性能进行了研究,并与基本差分进化算法进行了比较。实验表明,该算法在所有基准测试问题上均优于基本DE算法。

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