You are here

Home » Content

İSTANBUL HALK EKMEK A.Ş. (İHE)'YE AİT ÇOK DEPOLU ARAÇ ROTALAMA PROBLEMİNİN META-SEZGİSEL YÖNTEMLER İLE OPTİMİZASYONU

OPTIMIZATION OF MULTI-DEPOT VEHICLE ORUTING PROBLEM OF İSTANBUL HALK EKMEK A.S. (İHE) BY USING META-HEURISTIC METHODS

Journal Name:

  • Yönetim-İstanbul Üniversitesi İşletme Fakültesi İşletme İktisadı Enstitüsü Dergisi

Publication Year:

  • 2011

Key Words:

Keywords (Original Language):

Author NameUniversity of AuthorFaculty of Author
Abstract (2. Language): 
The Multi Depot Vehicle Routing Problem (MDVRP) is a well known and complex combinatorial problem which has received considerable attention in recent years. MDVRP can be described as the problem of designing optimal routes from several depots to a number of customers. The objective is to find a set of routes which minimizes the total distance traveled. In today's business world, transportation cost typically is an important part of the total logistics costs. An efficient heuristic method combining the genetic algorithm (GA) and particle swarm optimization (PSO) is proposed for solving clustering and VRP subproblems of the MDVRP. istanbul Halk Ekmek (İHE) A.S. is an economical organization established by the İstanbul Great City Municipality for producing and distributing cheap, healthy and high quality bread and floury products. The total daily capacity of the IHE factories (Cebeci, Edirnekapi, Kartal) is the production of more than 1 million breads (13% market share). IHE delivers bread to 1012 customers three times a day with 75 vehicles. The proposed GA-PSO based heuristic technic is used to solve the MDVRP of IHE A.S. and results are compared with the current delivery strategies.
Bookmark/Search this post with
Abstract (Original Language): 
Çok Depolu Araç Rotalama Problemi (ÇDARP) son yıllarda oldukça ilgi gören karmaşık bir kombinatoryal problemdir. ÇDARP birden fazla sayıda depodan birçok müşteriye ürün dağıtımına ait optimum rotaların tasarım problemidir. Toplam kat edilen mesafenin en küçüklenmesi problemin amaç denklemini oluşturmaktadır. Günümüz iş hayatında ürün dağıtım maliyetleri toplam lojistik maliyetlerinin önemli bir bölümünü oluşturmaktadır. Bu çalışmada Genetik Algoritma (GA) ve Parçacık Sürü Optimizasyonu (PSO) sezgisel teknikleri birlikte kullanılarak ÇDARP'nin kümeleme ve araç rotalama alt problemlerini etkin şekilde çözebilen bir sezgisel yöntem önerilmektedir. İstanbul Halk Ekmek (İHE) A.Ş. ucuz, sağlıklı ve yüksek kalitede ekmek ve ekmek ürünleri üretimi ve dağıtımı yapmak üzere İstanbul Büyük Şehir Belediyesi bünyesinde kurulan bir ticari organizasyondur. İHE fabrikalarının (Cebeci, Edirnekapı ve Kartal) toplam günlük üretim kapasitesi 1 milyon ekmektir ve İstanbul'un günlük ekmek ihtiyacının %13'unu karşılamaktadır. İHE'de dağıtımı gerçekleştiren 75 araç mevcuttur ve günde 3 kez 1012 müşteriye dağıtım yapılmaktadır. GA ve PSO birlikte kullanılarak İHE A.Ş.'nin çok depolu araç rotalama problemine optimum çözüm aranmıştır ve mevcut durum ile karşılaştırılmıştır.
FULL TEXT (PDF): 
PDF icon arastirmax-istanbul-halk-ekmek.s.iheye-ait-cok-depolu-arac-rotalama-probleminin-meta-sezgisel-yontemler-ile-optimizasyonu.pdf
  • 70
74-92
  • Turkish

REFERENCES

References: 

Aarts, E, Lenstra J.K., "Local Search In Combinatorial Optimization", John Wıley & Sons Ltd, 1997
Beasley,D., Bull D.R., Martin R.R., "An overview of genetic algorithms", University of Computing, 1993, 15(2), s:58-65
Chen, C.Y., Ye, F., "Particle Swarm Optimization Algorithm and Its Application to Clustering Analysis", Proceedings of the 2004 IEEE, International Conference of Networking, Sensing and Control, Taipei, Taiwan, March, 2004, s:789-795
Chiu, C.Y., Chen, Y.F., Kuo, I.T., Ku, H.C., "An Intelligent market segmentation system using k-means and particle swarm optimization", Expert Systems with Appications, 36, 2009, s: 4558-4565
Clerc, M., "Particle Swarm Optimization", 2006, UK, iste Publication
Colin Reeves, "Handbook of Metaheuristics, Chapter 3: Genetic Algorithm",
Derleyiciler: Glover, F., Kochenberger, G.A., Kluwer Academic Publishers, 2003, Dordrecht
Crevier, B., Cordeau, J. F., Laporte, G., "The multi-depot vehicle routing problem with inter-depot routes", European Journal of Operational Research, 176, 2007, s:756-773
Fealko, D. R., "Evaluating particle swarm intelligence techniques for solving university examination timetabling problems", Graduate School of Computer and Information Sciences, Nova Southeastern University, Doktora tezi, 2005, s:11
Goldberg, D. E., "Genetic Algorithms in Search, Optimization and Machine Learning," Addison-Wesley, 1989
Hassan, R., Cohanim, B., Weck, O., "A Comparison of Particle Swarm Optimization and The Genetic Algorithm", Structural Dynamics & Materials Conference 18-21 April 2005, Austin, Texas. s:1-13
91
Emrah Önder
Yönetim Yıl: 22 Sayı: 70 Ekim 2011
Ho, W., v.d., "A Hybrid genetic algorithm for the multi-depot vehicle routing problem", Engineering Application of Artificial Intelligence, 2007, s:550 Kennedy, J. and Eberhart, R. C, "Particle swarm optimization", Proc. of the IEEE International Conference on Neural Networks, vol.IV, 1995, s:1942-1948
Khoo, K. G., Suganthan, P. N., "Evaluation of genetic operators and solution representations for shape recognition by genetic algorithms", Pattern Recognition Letters, 23, 2002, s: 1589-1597
Laporte, Gilbert, Les Cahiers du GERAD, "The TSP, the VRP and their impact on combinatorial optimization", G-2009-57, s:6
Lawler, E. L., Lenstra, J.K., Rinnooy Kan, A.H.G, Shmoys, D. B., "The Traveling Salesman Problem: A Guided Tour of Combinatorial Optimization ", 1992
Paterlini, S., Krink T., "Differantial evoluation and particle swarm optimization in partitional clustering", Computational Statistics & Data Analysis, 50, 2006, s: 1220-1247
Shi, Y., Eberhart, R. C, "Emprical Study Of Particle Swarm Optimization",
Proceedings of the Congress on evolutionary Computation (CEC99) (July), 1999, s: 1945¬1950
Siriwardene, N. R., Perera, B. J. C, "Selection of genetic algorithm operators for urban drainage model parameter optimization", Mathematical and Computer Modelling, 44, 2006, s:415-429
Şevkli, M., Yenisey, M. M., "Atölye tipi çizelgeleme problemleri için parçacık sürü optimizasyonu yöntemi", İTÜ Dergisi, Mühendislik, Cilt:5, Sayı:2, Kısım: 1, Nisan 2006, s:58-68
Taniguchi, E., and Shimamoto, H., "Intelligent transportation system based dynamic vehicle routing and scheduling with variable travel times", Transportation Research Part C: Emerging Technologies, Volume 12, Issues 3-4, June-August 2004, s: 235-250
Tchomte, S. T., Gourgand, M., "Particle Swarm Optimization: A study of particle displacement for solving continuous and combinatorial optimization problems", Int. J. Production Economics, 121, 2009, s:57-67
Valle, Y.,v.d., "Particle Swarm Optimization:Basic Concepts, Variants and Applications in Power Systems", IEEE Transactions on Evolutionary Computation, Vol:12, No:2, April, 2008, s: 173
Xie, X. F., Zhang, W. J., Yang, Z. L., "A Dissipative Particle Swarm Optimization",
Congress on Evolutionary Computation (CEC), Hawaii, USA, 2002, s: 1456-1461

Thank you for copying data from http://www.arastirmax.com