旅行推销员问题的机器学习方法:综述

Umberto Junior Mele, Luca Maria Gambardella, R. Montemanni
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引用次数: 7

摘要

机器学习技术已经在很多领域得到了成功的应用。在这篇综述中,我们重点讨论了它们在组合优化(CO)领域的应用,特别是在旅行推销员问题(TSP)中的应用。我们提出了一个直观和简单的思维导图,有助于浏览广泛的现有文献,指出我们认为最有前途的方法。讨论和回顾了用于解决TSP的不同ML技术;他们的差异和局限性进行了深入研究。最后指出了该领域有待进一步研究的问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Machine Learning Approaches for the Traveling Salesman Problem: A Survey
Machine Learning techniques have been applied in many contexts with great success. In this survey, we focus on their applications in the Combinatorial Optimization (CO) domain, and in particular to the Traveling Salesman Problem (TSP). We propose an intuitive and simple mind map helpful to navigate through the wide existing literature, indicating the approaches we consider most promising. Different ML techniques introduced to solve the TSP are discussed and reviewed; and their differences and limitations are delved. Open problems for future research in this area are finally highlighted.
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