A Labelling Method for the Travelling Salesman Problem

Author:

Tawanda Trust1ORCID,Nyamugure Philimon1ORCID,Kumar Santosh2,Munapo Elias3

Affiliation:

1. Department of Statistics and Operations Research, National University of Science and Technology, Ascot, Bulawayo P.O. Box AC 939, Zimbabwe

2. Department of Mathematical and Geospatial Sciences, School of Sciences, RMIT University, Melbourne, VIC 3001, Australia

3. Department of Business Statistics and Operations Research, School of Economic Sciences, Mafikeng Campus, North West University, Mmabatho 2745, South Africa

Abstract

The travelling salesman problem (TSP) is a problem whereby a finite number of nodes are supposed to be visited exactly once, one after the other, in such a way that the total weight of connecting arcs used to visit these nodes is minimized. We propose a labelling method to solve the TSP problem. The algorithm terminates after K−1 iterations, where K is the total number of nodes in the network. The algorithm’s design allows it to determine alternative tours if there are any in the TSP network. The computational complexity of the algorithm reduces as iterations increase, thereby making it a powerful and efficient algorithm. Numerical illustrations are used to prove the efficiency and validity of the proposed algorithm.

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

Reference34 articles.

1. Sokkappa, P.R. (1991). The Cost-Constrained Traveling Salesman Problem. [Ph.D. Thesis, Stanford University].

2. A novel method for prize collecting traveling salesman problem with time windows. In Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation;Dogan;Proceedings of the INFUS 2021 Conference,2022

3. Venkatesh, P., Singh, A., and Mallipeddi, R. (2019, January 10–13). A multi-start iterated local search algorithm for the maximum scatter traveling salesman problem. Proceedings of the 2019 IEEE Congress on Evolutionary Computation (CEC), Wellington, New Zealand.

4. A simulated annealing algorithm for the vehicle routing problem with parcel lockers;Vincent;IEEE Access,2022

5. Tawanda, T., Nyamugure, P., Kumar, S., and Munapo, E. (2022). Intelligent Computing & Optimization: Proceedings of the 5th International Conference on Intelligent Computing and Optimization 2022 (ICO2022), Hua Hin, Thailand, 27–28 October2022, Springer International Publishing.

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