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Hierarchical Solving Method for Large Scale TSP Problems

机译:大规模TSP问题的分层求解方法

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This paper presents a hierarchical algorithm for solving large-scale traveling salesman problem (TSP), the algorithm first uses clustering algorithms to large-scale TSP problem into a number of small-scale collections of cities, and then put this TSP problem as a generalized traveling salesman problem (GTSP), convert solving large-scale TSP problem into solving GTSP and several small-scale TSP problems. Then all the sub-problems will be solved by ant colony algorithm and At last all the solutions of each sub-problem will be merged into the solution of the large-scale TSP problem by solution of GTSP. Experimental part we uses the traditional ant colony algorithm and new algorithm for solving large-scale TSP problem, numerical simulation results show that the proposed algorithm for large-scale TSP problem has a good effect, compared with the traditional ant colony algorithm, the solving efficiency has been significantly improved.
机译:本文提出了一种解决大规模旅行推销员问题(TSP)的分层算法,该算法首先使用聚类算法将大规模的TSP问题大量的城市集合,然后将此TSP问题作为广义的概括旅行推销员问题(GTSP),转换求解大规模TSP问题,以解决GTSP和几个小型TSP问题。然后,所有子问题将由蚁群算法解决,并且最后通过GTSP解决方案将每个子问题的解决方案合并为大规模TSP问题的解决方案。实验部分我们使用传统的蚁群算法和新算法来解决大规模的TSP问题,数值模拟结果表明,该算法的大规模TSP问题具有良好的效果,与传统的蚁群算法相比,解决效率得到了显着改善。

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