Mixed Mutation Strategy Embedded Differential Evolution

被引:21
作者
Pant, Millie [1 ]
Ali, Musrrat [1 ]
Abraham, Ajith [2 ]
机构
[1] Indian Inst Technol Roorkee, Saharanpur 247001, India
[2] Norwegian Univ Sci & Technol, Ctr Excellence Quantifiable Qual Serv, Norway & Machine Intelligence Res Labs, MIR Labs, Trondheim, Norway
来源
2009 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-5 | 2009年
关键词
differential evolution; mutation operator; mixed strategy;
D O I
10.1109/CEC.2009.4983087
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:1240 / +
页数:2
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