一种新的粒子群优化算法

2010 IEEE International Conference on Software Engineering and Service Sciences Pub Date : 2010-07-16 DOI:10.1109/ICSESS.2010.5552354

Wang Dongyun, Zeng Ping, Li Luowei, Wang Kai

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引用次数: 17

摘要

为了提高粒子群优化算法的性能，提出了一种基于平滑度和迭代的惯性权值动态变化的粒子群优化算法。用三个基准函数对新算法进行了测试。实验结果表明，该算法不仅可以摆脱局部最优，而且可以加快粒子的收敛速度，从而提高算法性能。

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A novel particle swarm optimization algorithm

A novel particle swarm optimization (NPSO) algorithm with dynamically changing inertia weight based on fltness and iterations was presented for improving the performance of the Particle Swarm Optimization algorithm. The new algorithm was tested with three benchmark functions. The experimental results show that the swarm can escape from local optimum, and it also can speed up the convergence of particles to improve the performance.

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2010 IEEE International Conference on Software Engineering and Service Sciences

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