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PARALLEL IMPLEMENTATION OF ANT COLONY OPTIMIZATION ON MPP

机译:MPP上蚁群优化的并行实现

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摘要

An adaptive parallel ant colony algorithm (PACO) is presented. In the algorithm, we propose a strategy for information exchange between processors which make each processor choose its partner to communicate and update the pheromone adaptively. We also propose a method of adjusting the time interval of information exchange adaptively according to the diversity of the solutions so as to increase the ability of search and avoid early convergence. Experimental results show that our algorithm PACO has high convergence speed, high speedup and efficiency.
机译:提出了一种自适应并行蚁群算法(PACO)。在该算法中,我们提出了一种用于处理器之间信息交换的策略,该策略使每个处理器选择其伙伴来自适应地通信和更新信息素。我们还提出了一种根据解决方案的多样性自适应地调整信息交换时间间隔的方法,以提高搜索能力并避免早期收敛。实验结果表明,该算法具有较高的收敛速度,较高的提速率和较高的效率。

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