An Improvement to the 2-Opt Heuristic Algorithm for Approximation of Optimal TSP Tour

The travelling salesman problem (TSP) is perhaps the most researched problem in the field of Computer Science and Operations. It is a known NP-hard problem and has significant practical applications in a variety of areas, such as logistics, planning, and scheduling. Route optimisation not only impro...

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Bibliographic Details
Published in:Applied sciences Vol. 13; no. 12; p. 7339
Main Authors: Uddin, Fakhar, Riaz, Naveed, Manan, Abdul, Mahmood, Imran, Song, Oh-Young, Malik, Arif Jamal, Abbasi, Aaqif Afzaal
Format: Journal Article
Language:English
Published: Basel MDPI AG 01.06.2023
Subjects:
Algorithms
Approximation
combinatorial optimisation
Computer science
Genetic algorithms
Greenhouse gases
Heuristic
heuristic algorithms
route optimisation
travelling salesman problem
TSPLIB
VRP
ISSN:2076-3417, 2076-3417
Online Access:Get full text
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Summary:The travelling salesman problem (TSP) is perhaps the most researched problem in the field of Computer Science and Operations. It is a known NP-hard problem and has significant practical applications in a variety of areas, such as logistics, planning, and scheduling. Route optimisation not only improves the overall profitability of a logistic centre but also reduces greenhouse gas emissions by minimising the distance travelled. In this article, we propose a simple and improved heuristic algorithm named 2-Opt++, which solves symmetric TSP problems using an enhanced 2-Opt local search technique, to generate better results. As with 2-Opt, our proposed method can also be applied to the Vehicle Routing Problem (VRP), with minor modifications. We have compared our technique with six existing algorithms, namely ruin and recreate, nearest neighbour, genetic algorithm, simulated annealing, Tabu search, and ant colony optimisation. Furthermore, to allow for the complexity of larger TSP instances, we have used a graph compression/candidate list technique that helps in reducing the computational complexity and time. The comprehensive empirical evaluation carried out for this research work shows the efficacy of the 2-Opt++ algorithm as it outperforms the other well-known algorithms in terms of the error margin, execution time, and time of convergence.
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ISSN:2076-3417
2076-3417
DOI:10.3390/app13127339