Solution of the Large-Scale Traveling Salesman Problem in the Context of the Complany's Logistics Strategy
https://doi.org/10.35596/1729-7648-2025-31-4-65-72
Abstract
This paper describes an approach based on reducing the large traveling salesman problem to a set of simpler ones. A solution algorithm is presented with a detailed illustration and a description of the logic behind the steps. The algorithm allows for repeated visits to cities, which is acceptable for practical purposes, since the primary objective is to find a route of minimal overall length, visiting each city at least once. A novel feature is the consideration of intra- and inter-cluster connections by recalculating the matrix of pairwise shortest distances between settlements. The initial network of settlements is then divided into clusters. Within each cluster, an optimal route is found that passes through all its nodes without returning to the starting node. The shortest route linking the clusters is then found. Taking this factor into account more clearly “separates” pairs of settlements in the resulting cluster structure, which facilitates obtaining high-quality solutions.
About the Authors
Yu. O. GermanBelarus
German Yuliya Olegovna, Cand. Sci. (Tech.), Associated Professor at the Department of Information Technologies of Automated Systems
220005, Minsk, Platonova St., 39
Tel.: +375 17 293-89-04
E. A. Semizhon
Belarus
Semizhon E. A., Assistant at the Computational Methods and Programming Department, Postgraduate
Minsk
References
1. Karakoyun M. (2019) A New Approach Based on K-Means Clustering and Shuffled Frog Leaping Algorithm to Solve Travelling Salesman Problem. Proceedings of the 7th International Symposium on Innovative Technologies in Engineering and Science, 22–24 Nov.
2. Land A. H., Doig A. G. (1960) Optimality and Infeasibility in Combinatorial Programming. Mathematical Programming. 1 (1), 122–136.
3. Bellman R. (1962) Dynamic Programming and Lattice Theory. Proceedings of the National Academy of Sciences. 48 (10), 2010–2015.
4. Croes G. A. (1958) The Traveling Salesman Problem. Operations Research. 6 (6), 791–812.
5. When Greedy Does Not Work – Traveling Salesman. Available: https://www.neeldhara.com/materials/cpnotes/w03/lec15 (Accessed 5 May 2025).
6. Luke S. (2011) Essentials of Metaheuristics. Lecture Notes. George Mason University. USA.
7. Sedgewick R., Wayne K. (2011) Algorithms. Addison Wesley. Available: https://algs4.cs.princeton.edu. (Accessed 21 October 2025).
8. Bishop M. C. (2006) Pattern Recognition and Machine Learning. Springer.
Review
For citations:
German Yu.O., Semizhon E.A. Solution of the Large-Scale Traveling Salesman Problem in the Context of the Complany's Logistics Strategy. Digital Transformation. 2025;31(4):65-72. (In Russ.) https://doi.org/10.35596/1729-7648-2025-31-4-65-72


















