Selective generalized travelling salesman problem

IF 1.8 4区数学 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Mathematical and Computer Modelling of Dynamical Systems Pub Date : 2020-01-02 DOI:10.1080/13873954.2019.1705496

Tusan Derya, Esra Dinler, Barış Keçeci

引用次数: 6

Abstract

ABSTRACT This paper introduces the Selective Generalized Traveling Salesman Problem (SGTSP). In SGTSP, the goal is to determine the maximum profitable tour within the given threshold of the tour’s duration, which consists of a subset of clusters and a subset of nodes in each cluster visited on the tour. This problem is a combination of cluster and node selection and determining the shortest path between the selected nodes. We propose eight mixed integer programming (MIP) formulations for SGTSP. All of the given MIP formulations are completely new, which is one of the major novelties of the study. The performance of the proposed formulations is evaluated on a set of test instances by conducting 4608 experimental runs. Overall, 4138 out of 4608 (~90%) test instances were solved optimally by using all formulations.

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选择性广义旅行商问题

本文介绍了选择性广义旅行商问题(SGTSP)。在SGTSP中，目标是在给定的巡回持续时间阈值内确定最有利可图的巡回，该巡回由集群子集和巡回中访问的每个集群中的节点子集组成。这个问题结合了集群和节点的选择，以及确定所选节点之间的最短路径。我们提出了SGTSP的8种混合整数规划(MIP)公式。所有给定的MIP配方都是全新的，这是该研究的主要新颖之处之一。通过进行4608次实验运行，在一组测试实例上评估了所建议配方的性能。总的来说，4608个测试实例中有4138个(约90%)通过使用所有配方得到了最佳解决。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Mathematical and Computer Modelling of Dynamical Systems 数学-计算机：跨学科应用

CiteScore

3.80

自引率

5.30%

发文量

审稿时长

>12 weeks

期刊介绍： Mathematical and Computer Modelling of Dynamical Systems (MCMDS) publishes high quality international research that presents new ideas and approaches in the derivation, simplification, and validation of models and sub-models of relevance to complex (real-world) dynamical systems. The journal brings together engineers and scientists working in different areas of application and/or theory where researchers can learn about recent developments across engineering, environmental systems, and biotechnology amongst other fields. As MCMDS covers a wide range of application areas, papers aim to be accessible to readers who are not necessarily experts in the specific area of application. MCMDS welcomes original articles on a range of topics including: -methods of modelling and simulation- automation of modelling- qualitative and modular modelling- data-based and learning-based modelling- uncertainties and the effects of modelling errors on system performance- application of modelling to complex real-world systems.