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| A Particle Swarm Algorithm for MultiObjective Optimization Problem |
| JIANG Hao, ZHENG JinHua, CHEN LiangJun |
| Institute of Information Engineering, Xiangtan University, Xiangtan 411105 |
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Abstract A new multiobjective particle swarm optimization (MOPSO) based on enhanced εdominance is proposed, which keeps good diversity. A new idea named guide mutation is introduced to select global guide from the archive. Then a population updating strategy and selfadaptive mutation operation are shown to speed up convergence. Experimental results show that the proposed approach has effective and steadystate performance and is simple to implement.
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Received: 07 August 2006
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2007, Vol. 20 
