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General Information
    • ISSN: 1793-8236 (Online)
    • Abbreviated Title Int. J. eng. technol.(Online)
    • Frequency:  Bimonthly
    • DOI: 10.7763/IJET
    • Executive Editor: Ms.Yoyo Y. Zhou
    • Abstracting/ Indexing: Chemical Abstracts Services (CAS) EBSCO, Google Scholar, Ulrich Periodicals Directory, Crossref, ProQuest, Index CopernicusEI (INSPEC, IET).
    • E-mail: ijet@vip.163.com
Editor-in-chief
Prof. T. Hikmet Karakoc
Anadolu University, Faculty of Aeronautics and Astronautics, Turkey

IJET 2018 Vol.10(3): 254-258 ISSN: 1793-8236
DOI: 10.7763/IJET.2018.V10.1069

A Hybrid Model Of Max-Min Ant System with Genetic Algorithm For Improved To Travelling Salesman Problem

Tuncay Aydoğan and Raed Al-Badri
Abstract—Travelling Salesman Problem (TSP) is one of the oldest combinatorial problems that are classified as NP-hard. Hence, solving this type of problems requires a tremendous number of computational complexities by an intensive search process. Though TSP is an old problem, it is still the attractive spot of study for many researchers due to using in its many applications. The TSP problem is tackled by using a new hybrid algorithm approach in this work. This hybrid approach is applied with Genetic Algorithm (GA) that invokes Max-Min Ant System (MMAS) algorithm to minimize the cost, called HGAMMAS. In the experimental results of HGAMMAS reached to BKS(Best Known Solution) values using TSPLIB.

Index Terms—TSP, genetic algorithm, max-min ant system algorithm, hybrid algorithm.

Tuncay Aydoğan is with the Department of Software Engineering, Suleyman Demirel University, 32260, Turkey (e-mail: tuncayaydogan@sdu.edu.tr).
Raed Al-Badri was with the Department of Computer Engineering, Suleyman Demirel University, 32260, Turkey (e-mail: raed.albadri@gmail.com).

[PDF]

Cite: Tuncay Aydoğan and Raed Al-Badri, "A Hybrid Model Of Max-Min Ant System with Genetic Algorithm For Improved To Travelling Salesman Problem," International Journal of Engineering and Technology vol. 10, no. 3, pp. 254-258, 2018.

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