粒子群优化中的劳动分工

Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600) Pub Date : 2002-05-12 DOI:10.1109/CEC.2002.1004476

J. Vesterstrom, J. Riget, T. Krink

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引用次数: 85

摘要

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。

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Division of labor in particle swarm optimisation

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.

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Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600)

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