粒子群优化算法的多相泛化

Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600) Pub Date : 2002-05-12 DOI:10.1109/CEC.2002.1006283

B. Al-kazemi, C. Mohan

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引用次数: 64

摘要

多相粒子群优化算法是一种用于求解离散和连续问题的新算法。在该算法中，不同的粒子组在算法的不同阶段具有不同目标的轨迹。在一些基准问题上，该算法优于标准粒子群优化、遗传算法和进化规划。

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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Multi-phase generalization of the particle swarm optimization algorithm

Multi-phase particle swarm optimization is a new algorithm to be used for discrete and continuous problems. In this algorithm, different groups of particles have trajectories that proceed with differing goals in different phases of the algorithm. On several benchmark problems, the algorithm outperforms standard particle swarm optimization, genetic algorithm, and evolution programming.

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

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