A matheuristic approach for the family traveling salesman problem

IF 1.1 4区计算机科学 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Journal of Heuristics Pub Date : 2023-09-22 DOI:10.1007/s10732-023-09516-9

Abtin Nourmohammadzadeh, Malek Sarhani, Stefan Voß

引用次数: 0

Abstract

Abstract In the family traveling salesman problem (FTSP), there is a set of cities which are divided into a number of clusters called families. The salesman has to find a shortest possible tour visiting a specific number of cities from each of the families without any restriction of visiting one family before starting the visit of another one. In this work, the general concept of the Partial OPtimization Metaheuristic Under Special Intensification Conditions is linked with the exact optimization by a classical solver using a mathematical programming formulation for the FTSP to develop a matheuristic. Moreover, a genetic and a simulated annealing algorithm are used as metaheuristics embedded in the approach. The method is examined on a set of benchmark instances and its performance is favorably compared with a state-of-the-art approach from literature. Moreover, a careful analysis of the specific components of the approach is undertaken to provide insights into the impact of their interplay.

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家庭旅行商问题的数学方法

在家庭旅行商问题(FTSP)中，存在一组城市，这些城市被划分为许多称为家庭的簇。销售人员必须找到一个最短的行程，从每个家庭中访问特定数量的城市，而不受访问一个家庭之前开始访问另一个家庭的限制。在本文中，将特殊强化条件下的部分优化元启发式的一般概念与经典求解器的精确优化联系起来，利用数学规划公式对FTSP进行数学求解。此外，采用遗传和模拟退火算法作为嵌入该方法的元启发式算法。该方法在一组基准实例上进行了测试，其性能优于文献中最先进的方法。此外，还对该方法的具体组成部分进行了仔细分析，以便深入了解其相互作用的影响。

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

Journal of Heuristics 工程技术-计算机：理论方法

CiteScore

5.80

自引率

0.00%

发文量

审稿时长

6 months

期刊介绍： The Journal of Heuristics provides a forum for advancing the state-of-the-art in the theory and practical application of techniques for solving problems approximately that cannot be solved exactly. It fosters the development, understanding, and practical use of heuristic solution techniques for solving business, engineering, and societal problems. It considers the importance of theoretical, empirical, and experimental work related to the development of heuristics. The journal presents practical applications, theoretical developments, decision analysis models that consider issues of rational decision making with limited information, artificial intelligence-based heuristics applied to a wide variety of problems, learning paradigms, and computational experimentation. Officially cited as: J Heuristics Provides a forum for advancing the state-of-the-art in the theory and practical application of techniques for solving problems approximately that cannot be solved exactly. Fosters the development, understanding, and practical use of heuristic solution techniques for solving business, engineering, and societal problems. Considers the importance of theoretical, empirical, and experimental work related to the development of heuristics.