Genetic Algorithms for the Travelling Salesman Problem: A Crossover Comparison

Tariq ALQURA'N ALZYADAT, Mohammad Yamin, Girija CHETTY

Research output: A Conference proceeding or a Chapter in BookConference contribution

Abstract

This paper addresses the use of Genetic Algorithms (GA) in solving the Travelling Salesman Problem (TSP), it compares the results of implementing two different approaches of ‘Order Crossover 1’ genes crossover, the static and the random position 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
Title of host publicationProceedings of the 11th INDIACom
EditorsDr. M.N. Hoda
Place of PublicationNew Delhi, India
PublisherBVICAM
Pages1465-1469
Number of pages5
ISBN (Electronic)9789380544243
Publication statusPublished - 8 Mar 2017
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

Conference

Conference11th INDIACom
CountryIndia
CityNew Delhi
Period1/03/173/03/17

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    ALQURA'N ALZYADAT, T., Yamin, M., & CHETTY, G. (2017). Genetic Algorithms for the Travelling Salesman Problem: A Crossover Comparison. In D. M. N. Hoda (Ed.), Proceedings of the 11th INDIACom (pp. 1465-1469). BVICAM. https://www.bvicam.ac.in/news/INDIACom%202017%20Proceedings/Main/papers/270.pdf