Genetic Algorithms for the Travelling Salesman Problem: A Crossover Comparison

Tariq Alzyadat, Mohammad Yamin, Girija Chetty

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)


This paper addresses an application of genetic algorithms (GA) for solving the travelling salesman problem (TSP), it compares the results of implementing two different types of two-point (1 order) genes crossover, the static and the dynamic approaches, which are used to produce new offspring. By changing three factors; the number of cities, the number of generations and the population size, the goal is to show which approach is better in terms of finding the optimal solution (the shortest path) in as short time as possible as a result of these changes. Besides, it will explore the effect of changing the above factors on finding the optimal solution.

Original languageEnglish
Pages (from-to)209-213
Number of pages5
JournalInternational Journal of Information Technology
Issue number1
Publication statusPublished - Mar 2020
Event11th INDIACom: 2017 4th International Conference on Computing for Sustainable Global Development - Bharati Vidyapeeth's Institute of Computer Applications and Management (BVICAM), New Delhi, India
Duration: 1 Mar 20173 Mar 2017
Conference number: 40353


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