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A Modified Differential Evolution Algorithm and Its Application to Engineering Problems

机译:修改的差分演进算法及其在工程问题中的应用

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In the present study a Modified Differential Evolution (MDE) algorithm is proposed. This algorithm is different in three ways from basic DE. For initialization it utilizes opposition-based learning while in basic DE uniform random numbers serve this task. Secondly, in basic DE mutant individual is random while in MDE it is tournament best and finally MDE utilizes only one set of population as against two sets as used in basic DE. 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 and real life applications
机译:在本研究中,提出了一种修改的差分演进(MDE)算法。此算法以基本DE的三种方式不同。对于初始化,它利用基于反对的学习,而在基本的de统一的随机数中提供此任务。其次,在基本的de突变体中是随机的,而在MDE中,它是最佳锦标赛,最后MDE只利用一组人口,与基本de中使用的两组。研究了所提出的算法的性能,并与基本差分演变进行了比较。进行的实验表明,所提出的算法在所有基准问题和现实生活应用中表现出基本的基本算法

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