多目标优化问题的异步自调节岛遗传算法

Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600) Pub Date : 2002-05-12 DOI:10.1109/CEC.2002.1007034

Zhong-Yao Zhu, K. Leung

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引用次数: 21

摘要

本文提出了一种求解多目标优化问题的新算法——异步自调节岛遗传算法(aSAIGA)。该算法建立在粗粒度体系结构之上，该体系结构被划分为子进程并分布在多个孤岛处理器中。在每个子过程中，采用异步通信运算和自调整运算，增强了算法的加速能力和全局搜索能力。仿真结果表明，采用aSAIGA可以获得满意的结果和显著的加速。

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Asynchronous self-adjustable island genetic algorithm for multi-objective optimization problems

In this paper, we present a new algorithm-asynchronous self-adjustable island genetic algorithm (aSAIGA) for multi-objective optimization problems. The proposed algorithm is built upon the coarse-grained architecture, which is divided into sub-processes and distributed amongst several island processors. In each sub-process, an asynchronous communication operation and a self-adjusting operation are adopted to enhance the algorithm in both speedup and global searching capabilities. Satisfactory results and significant speedup can be achieved by aSAIGA, as shown by simulation.

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

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