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A study of a parallelized immune coevolutionary algorithm for division-of-labor problems

机译:分工问题的并行免疫协同进化算法研究

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Recently, a number of parallelized optimization algorithms have been proposed. We have proposed a co-evolutionary immune algorithm (IA) to solve the division-of-labor problems, in particular the n-th agents travelling salesman problem (n-TSP). In this article, we extend the co-evolutionary IA for a large-scale n-TSP with (1) an improvement for the search speed through parallelized search on the PC-cluster, and (2) the introduction of a new division-processing pre-estimated division processing to improve the search ability. Some computational experiments show the proposed method can obtain better quality solutions for division-of-labor problems, and present an applicable parameter cofinguration.
机译:最近,已经提出了许多并行优化算法。我们提出了一种协同进化免疫算法(IA)来解决分工问题,尤其是第n个代理商旅行商问题(n-TSP)。在本文中,我们将协同进化IA扩展到大规模n-TSP,其中(1)通过在PC群集上并行搜索提高搜索速度,以及(2)引入新的除法处理预先估计分割处理以提高搜索能力。一些计算实验表明,该方法可以较好地解决分工问题,并给出了适用的参数共构关系。

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