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Bi-criteria travelling salesman subtour problem with time threshold

机译:双标准旅行推销员子系统的时间阈值

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This paper deals with the bi-criteria travelling salesman subtour problem with time threshold (BTSSP-T), which comes from the family of the travelling salesman problem (TSP) and is NP-hard in the strong sense. The problem arises in several application domains, mainly in routing and scheduling contexts. Here, the model focuses on two criteria: total travel distance and gains attained. The BTSSP-T aims to determine a subtour that starts and ends at the same city and visits a subset of cities at a minimum travel distance with maximum gains, such that the time spent on the tour does not exceed the predefined time threshold. A zero-one integer-programming problem is adopted to formulate this model with all practical constraints, and it includes a finite set of feasible solutions (one for each tour). Two algorithms, namely, the Lexi-Search Algorithm (LSA) and the Tabu Search (TS) algorithm have been developed to solve the BTSSP-T problem. The proposed LSA implicitly enumerates the feasible patterns and provides an efficient solution with backtracking, whereas the TS, which is metaheuristic, will give the better approximate solution. A numerical example is demonstrated in order to understand the search mechanism of the LSA. Numerical experiments are carried out in the MATLAB environment, on the different benchmark instances available in the TSPLIB domain as well as on randomly generated test instances. The experimental results show that the proposed LSA works better than the TS algorithm in terms of solution quality and, computationally, both LSA and TS are competitive.
机译:本文涉及与时间阈值(BTSSP-T)的双标准旅行推销员副问题,这来自旅行推销员问题(TSP)的家族,并且在强烈的意义上是NP难的。问题在几个应用程序域中出现,主要是在路由和调度上下文中。在这里,该模型侧重于两个标准:总行程距离和获得的增益。 BTSSP-T旨在确定在同一城市开始和结束的子场,并在最大的行驶距离中访问城市的子集,最大收益,使得在巡回演出上的时间不超过预定义的时间阈值。采用零一个整数编程问题来制定具有所有实际约束的该模型,它包括一个有限的可行解决方案(每个旅行中的一个)。已经开发出两种算法,即Lexi-Search算法(LSA)和禁忌搜索(TS)算法来解决BTSSP-T问题。所提出的LSA隐式枚举可行模式并提供有效的解决方案,而具有回溯,而成群质造型的TS将提供更好的近似解。为了理解LSA的搜索机制,证明了数值示例。在MATLAB环境中执行数值实验,在TSPLIB域中提供的不同基准实例以及随机生成的测试实例。实验结果表明,在解决方案质量方面,所提出的LSA优于TS算法,并计算地,LSA和TS都具有竞争力。

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