Adaptive multi-objective differential evolution with stochastic coding strategy

  title={Adaptive multi-objective differential evolution with stochastic coding strategy},
  author={Jinghui Zhong and Jun Zhang},
Many real-world applications can be modeled as multi-objective optimization problems (MOPs). Applying differential evolution (DE) to MOPs is a promising research topic and has drawn a lot of attention in recent years. To search high-quality solutions for MOPs, this paper presents a robust adaptive DE (termed AS-MODE) with following two features. First, a stochastic coding strategy is used to improve the solution quality. This coding strategy represents each individual by a stochastic region… CONTINUE READING
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Multiobjective Optimization Test Instances for the CEC2009 Special Session and Competition

  • Q. F. Zhang, A. Zhou, S. Z. Zhao, P. N. Suganthan, W. Liu, S. Tiwari
  • Special Session on Performance Assessment of…
  • 2008
Highly Influential
8 Excerpts

DE’s selection rule for multiobjective optimization

  • J. Lampinen
  • Lappeenranta University of Technology, Department…
  • 2001
Highly Influential
10 Excerpts

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