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A New Particle Swarm Optimizer with Cooperative Coevolution for Large Scale Optimization

机译:一种新的粒子群优化器,具有用于大规模优化的合作协作

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With the increasing demands in solving larger dimensional problems,it is necessary to have efficient algorithm. Efforts were put towards increasing the efficiency of the algorithms. This paper presents a new approach of particle swarm optimization with cooperative coevolution. The proposed technique [NPSO-CC] is built on the success of an early CCPSO2 that employs an effective variable grouping technique random grouping. The technique of moving away out of the local minima is presented in the paper. Instead of using simple velocity update equation, the new velocity update equation is used from where the contribution of worst particle is subtracted. Experimental results show that our algorithm performs better as compared to other promising techniques on most of the functions.
机译:随着求解较大维度问题的需求越来越大,有必要具有有效的算法。努力提高算法的效率。本文介绍了具有合作协作粒子群优化的新方法。所提出的技术[NPSO-CC]建立在采用有效变量分组技术随机分组的早期CCPSO2的成功。纸张中提出了将远离局部最小值移出的技术。不是使用简单的速度更新方程,从而从减去最坏粒子的贡献的位置使用新的速度更新等式。实验结果表明,与大多数功能的其他有希望的技术相比,我们的算法表现更好。

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