Machine Learning Constructives and Local Searches for the Travelling Salesman Problem

Tommaso Vitali, Umberto Junior Mele (), Luca Maria Gambardella and Roberto Montemanni
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Tommaso Vitali: Università della Svizzera Italiana
Umberto Junior Mele: Università della Svizzera Italiana
Luca Maria Gambardella: Università della Svizzera Italiana
Roberto Montemanni: University of Modena and Reggio Emilia

A chapter in Operations Research Proceedings 2021, 2022, pp 59-65 from Springer

Abstract: Abstract The ML-Constructive heuristic is a recently presented method and the first hybrid method capable of scaling up to real scale traveling salesman problems. It combines machine learning techniques and classic optimization techniques. In this paper we present improvements to the computational weight of the original deep learning model. In addition, as simpler models reduce the execution time, the possibility of adding a local-search phase is explored to further improve performance. Experimental results corroborate the quality of the proposed improvements.

Keywords: Travelling Salesman Problem; Machine learning; Hybrid heuristic; Combinatorial optimization; Artificial intelligence (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/978-3-031-08623-6_10

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