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A MuIti-Objective Memetic Optimization AIgorithm Based on EcoIogicaI PopuIation Preying-Competition ModeI
Author(s): 
Pages: 1488-1498
Year: Issue:  8
Journal: Acta Electronica Sinica

Keyword:  multi-objective optimizationpreying-competitionevolutionary algorithmMemetic computation;
Abstract: Aiming at the difficulty of searching Pareto front for complex multi-objective optimization,a Memetic learning strategy which combines many of population preying-competition mechanism with reinforcement learning mechanism and evolution-ary computation model was designed.Inspired by ecological principle,such as the population evolution and the competition between predator populations and prey populations,a multi-objective Memtic optimization algorithm (multi-objective Memetic algorithm based on ecological population preying-competition model,ECPM-MOMA)was proposed.In ECPM-MOMA,Preying-competition and Reinforcement Learning operator was designed and applied for global search.Memetic search operator was also applied for local search in the population evolution process.Experimental results show that the proposed algorithm has better convergence perfor-mance and distribution characteristics.The ecological preying-competition strategy and evolutionary computation model is effective for solving complex multi-objective optimization problems.
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