METAHEURISTIC ALGORITHMS FOR SOLVING VEHICLE ROUTING PROBLEMS

Vehicle Routing Problem is the most important problem in distribution systems and it has lots of application. Basically, exact and heuristic methods are used to solve such problems. Heuristic methods for solving the Vehicle Routing Problems are divided into two main groups; classical heuristic and meta-heuristic methods. In this paper, a metaheuristic method described and the results of this research shows that presenting the “Use and practice of metaheuristic algorithms for solving vehicle routing problems”.

METAHEURISTIC ALGORITHMS FOR SOLVING VEHICLE ROUTING PROBLEMS

Vehicle Routing Problem is the most important problem in distribution systems and it has lots of application. Basically, exact and heuristic methods are used to solve such problems. Heuristic methods for solving the Vehicle Routing Problems are divided into two main groups; classical heuristic and meta-heuristic methods. In this paper, a metaheuristic method described and the results of this research shows that presenting the “Use and practice of metaheuristic algorithms for solving vehicle routing problems”

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  • Clarke, G., Wright, J.W. Scheduling of Vehicles from a Central Depot to a Number of Delivery Points, Operations Research, 1964, c. 12, sf. 568-581.
  • Çalışkan, E., Acar, H., Akay, A.E. Odun Hammadesi Taşımacılığında Meta-Sezgisel Yöntemlerin Kullanımı. Artvin Çoruh Üniversitesi Orman Fakültesi Dergisi. – 2009. – 10 (1). – S.19-28.
  • Dantzig, G. and Ramser, J. The truck dispatching problem.Management Science. – 1959. – 6(1). – Pp.80-91.
  • Demircioğlu, M. Araç Rotalama Probleminin Sezgisel Bir Yaklaşım İle Çözümlenmesi Üzerine Bir Uygulama. Çukurova Üniversitesi, Doktora Tezi, 2009.
  • Glover, F. and Laguna, M. Tabu search. Boston: Kluwer Academic Publishers, 1997.
  • Goldenberg, D.E. Genetic Algorithms in Search Optimization, and Machine Learning’, Addison-Wesley, New York, USA, 1989. – 411p.
  • Hertz, A., Widmer, M. Guidelines for the Use of Meta-Heuristics ın Combinatorial Optimization // European Journal of Operation Research, 2004.
  • Kennedy, J. and Eberhart, R. Particle swarm optimization. Neural Networks Proceedings IEEE International Conference on, Perth, 1942-1948, 1995.
  • Kirkpatrick, S., Gellat, C.D. and Vecchi, M.P. Optimization by Simulated Annealing // Science, New Series, 1983. –Vol.220, No.4598. – Pp. 671-680.
  • Nabiyev, V.V. Yapay Zeka – Problemler Yöntemler Algoritmalar, Seçkin Yayınevi, Ankara, 2003.
  • Öztemel, Ercan. Yapay Sinir Ağları. Papatya Yayıncılık, İstanbul, 2012.
  • Söke, A., Bingül, Z. İki Boyutlu Giyotinsiz Kesme Problemlerinin Benzetilmiş Tavlama Algoritması ile Çözümlerinin İncelenmesi. Politeknik Dergisi. Cilt, 2005. – 8 s.
  • Tokaylı, M.A. Zaman Pencereli Araç Rotalama Problemi için Bir Karar Destek Sistemi, Yüksek Lisans Tezi, Gazi Üniversitesi, 2005.
  • Toth, P., Vigo, D. The Vehicle Routing Problem // Society for Industrial and Applied Mathematics, Philadelphia, 2002.
  • Yücenur, G.N., Demirel, N.Ç. A Hybrid Algorithm with Genetic Algorithm and Ant Colony Optimization for Solving Multi-Depot Vehicle Routing Problems // Journal of Engineering and Natural Sciences. – 2011. – Sigma 29. – Pp. 340-350.
  • Урдалетова, А.Б., Абдылдаев, М.М. М.Рыскулбеков атындагы Кыргыз Экономикалык Университетинин Кабарлары. – Бишкек, 2015. – 4(34). – Б. 63-67.