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| WEI Zhen, WU Lei, GE Fang-Zhen, WANG Qiang |
| School of Computer and Information,Hefei University of Technology,Hefei 230009 |
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Abstract A hybrid PSO algorithm based on memetic framework (HM-PSO) is proposed. It helps the particles which have certain leaning capacity accelerate convergence rate by Lamarckian Learning based local search strategy and helps the particles which fall into the local optimum escape from local optimum by Tabu search. HM-PSO avoids falling into the local optimum by enhancing the diversity of swarm with accelerating convergence rate. The experimental results show that the improved Lamarckian Learning strategy is effective and feasible and HM-PSO is an effective optimization algorithm with better global search performance.
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Received: 22 November 2010
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2012, Vol. 25 
