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A self-adaptive linear evolutionary algorithm for solving constrained optimization problems
Received:2008/12/20  Revised:2009/7/8
Keywords:Multiobjective optimization  Evolutionary algorithms  Pareto optimal solution  Linear fitness function
Fund Project:This work was supported by the National Natural Science Foundation of China (No.60803049, 60472060).
AuthorInstitutionE-mail
Kezong TANG School of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing Jiangsu 210094, China tangkezong@126.com 
Jingyu YANG School of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing Jiangsu 210094, China  
Shang GAO School of Computer Science and Engineering, Jiangsu University of Science and Technology, Zhenjiang Jiangsu 212003, China  
Tingkai SUN School of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing Jiangsu 210094, China  
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Abstract:
      In many real-world applications of evolutionary algorithms, the fitness of an individual requires a quantitative measure. This paper proposes a self-adaptive linear evolutionary algorithm (ALEA) in which we introduce a novel strategy for evaluating individuals relative strengths and weaknesses. Based on this strategy, searching space of constrained optimization problems with high dimensions for design variables is compressed into two-dimensional performance space in which it is possible to quickly identify good individuals of the performance for a multiobjective optimization application, regardless of original space complexity. This is considered as our main contribution. In addition, the proposed new evolutionary algorithm combines two basic operators with modification in reproduction phase, namely, crossover and mutation. Simulation results over a comprehensive set of benchmark functions show that the proposed strategy is feasible and effective, and provides good performance in terms of uniformity and diversity of solutions.
Kezong TANG,Jingyu YANG,Shang GAO and Tingkai SUN.A self-adaptive linear evolutionary algorithm for solving constrained optimization problems[J].Journal of Control Theory and Applications,2010,8(4):533~539.
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