Division of labor in particle swarm optimisation

J. Vesterstrom, J. Riget, T. Krink
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引用次数: 85

Abstract

We introduce Division of Labor (DoL) from social insects to improve local optimisation of the Particle Swarm Optimiser (PSO). We compared the performance with the basic PSO, a GA and simulated annealing and found improvements around local optima. The PSO with DoL outperforms the basic PSO on most testcases and is comparable in local optimisation with SA.
粒子群优化中的劳动分工
为了改进粒子群优化器(PSO)的局部优化,我们引入了社会性昆虫的劳动分工(DoL)。我们将其性能与基本粒子群算法、遗传算法和模拟退火算法进行了比较,并在局部最优处发现了改进。具有DoL的粒子群在大多数测试用例中优于基本粒子群,并且在局部优化方面与SA相当。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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