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Iterated two-phase local search for the colored traveling salesmen problem
Engineering Applications of Artificial Intelligence ( IF 8 ) Pub Date : 2020-11-01 , DOI: 10.1016/j.engappai.2020.104018
Pengfei He , Jin-Kao Hao

The colored traveling salesmen problem (CTSP) is a generalization of the popular traveling salesman problem with multiple salesmen. In CTSP, the cities are divided into m exclusive city sets (m is the number of salesmen) and one shared city set. The goal of CTSP is to determine a shortest Hamiltonian circuit (also called route or tour) for each of the m salesmen satisfying that (1) each route includes all cities of an exclusive city set and some (or all) cities of the shared city set, and (2) each city of the shared city set is included in one unique route. CTSP is a relevant model for a number of practical applications and is known to be computationally challenging. We present the first iterated two-phase local search algorithm for this important problem which combines a local optima exploration phase and a local optima escaping phase. We show computational results on 65 common benchmark instances to demonstrate its effectiveness and especially report 22 improved upper bounds. We make the source code of the algorithm publicly available to facilitate its use in future research and real applications.



中文翻译:

迭代两阶段本地搜索有色旅行商问题

有色旅行推销员问题(CTSP)是具有多个推销员的流行旅行推销员问题的推广。在CTSP中,城市分为 独家城市套装(是销售人员的数量)和一个共享城市集。CTSP的目标是为每条路线确定最短的哈密顿回路(也称为路线或游览路线)满足以下条件的推销员:(1)每条路线都包括专属城市集的所有城市和共享城市集的一些(或全部)城市,并且(2)共享城市集的每个城市都包含在一条唯一的路线中。CTSP是用于许多实际应用的相关模型,并且已知在计算上具有挑战性。针对此重要问题,我们提出了第一种迭代的两阶段局部搜索算法,该算法结合了局部最优探索阶段和局部最优逃避阶段。我们在65个常见基准实例上显示了计算结果,以证明其有效性,尤其是报告了22个改进的上限。我们公开该算法的源代码,以方便其在未来的研究和实际应用中使用。

更新日期:2020-11-02
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