Two Improvement Strategies for PSO

Abstract : This paper proposed an improved particle swarm optimization algorithm (IPSO) to solve continuous function optimization problems. Two improvement strategies named "Vector correction strategy" and "Jump out of local optimum strategy" were employed in our improved algorithm. The algorithm was tested using 25 newly proposed benchmark instances in Congress on Evolutionary Computation 2005 (CEC2005). The experimental results show that the search efficiency and the ability of jumping out from the local optimum of the IPSO have been significantly improved, and the improvement strategies are effective.
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Zhongzhi Shi; Sunil Vadera; Agnar Aamodt; David Leake. 6th IFIP TC 12 International Conference on Intelligent Information Processing (IIP), Oct 2010, Manchester, United Kingdom. Springer, IFIP Advances in Information and Communication Technology, AICT-340, pp.122-129, 2010, Intelligent Information Processing V. 〈10.1007/978-3-642-16327-2_17〉
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Quansheng Dou, Shasha Liu, Ping Jiang, Xiuhua Zhou, Zhongzhi Shi. Two Improvement Strategies for PSO. Zhongzhi Shi; Sunil Vadera; Agnar Aamodt; David Leake. 6th IFIP TC 12 International Conference on Intelligent Information Processing (IIP), Oct 2010, Manchester, United Kingdom. Springer, IFIP Advances in Information and Communication Technology, AICT-340, pp.122-129, 2010, Intelligent Information Processing V. 〈10.1007/978-3-642-16327-2_17〉. 〈hal-01055064〉

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