欧氏有界多重旅行推销员问题的算法

Víctor Pacheco-Valencia, Nodari Vakhania
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摘要

在有界多重旅行推销员问题(BMTSP)中,需要为每个推销员建立一个起点和终点都在仓库的旅行线路,并遵守可行的推销员旅行线路应满足的城市数量限制。目标是最小化所有旅行的总长度。我们提出了一种欧氏 BMTSP 的三阶段启发式算法。我们测试了该算法的 22 个基准实例和我们创建的 168 个新问题实例。我们报告了 22 个基准实例的 19 个已知最优解,其中包括 12 个最大解。对于新创建的实例,我们将我们算法的性能与 ILP 求解器 CPLEX 的性能进行了比较,后者能够在我们规定的两小时时限内为 71% 的实例构建可行的解决方案。对于大约 10%的最小新实例,CPLEX 提供了略好的解决方案,而我们的算法对于其中最大的实例只用了不到 180 秒。对于 CPLEX 所求解的其余 61% 的实例,我们的启发式算法的求解结果平均比 CPLEX 的求解结果好 21.5%。
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An Algorithm for the Euclidean Bounded Multiple Traveling Salesman Problem
In the Bounded Multiple Traveling Salesman Problem (BMTSP), a tour for each salesman, that starts and ends at the depot and that respects the bounds on the number of cities that a feasible salesman tour should satisfy, is to be constructed. The objective is to minimize the total length of all tours. Already Euclidean traveling salesman problem is NP-hard. We propose a 3-Phase heuristic algorithm for the Euclidean BMTSP. We tested the algorithm for the 22 benchmark instances and 168 new problem instances that we created. We report 19 best known solutions for the 22 benchmark instances including the 12 largest ones. For the newly created instances, we compared the performance of our algorithm with that of an ILP-solver CPLEX, which was able to construct a feasible solution for 71% of the instances within the time limit of two hours imposed by us. For about 10% of the smallest new instances, CPLEX delivered slightly better solutions, where our algorithm took less than 180 seconds for the largest of these instances. For the remaining 61% of the instances solved by CPLEX, the solutions by our heuristic were, on average, about 21.5% better than those obtained by CPLEX.
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