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P-Medyan kuruluş yeri seçim probleminin çözümünde parçacık sürü optimizasyonu algoritması yaklaşımı

Journal Name:

  • İstanbul Üniversitesi İşletme Fakültesi Dergisi

Publication Year:

  • 2012

Key Words:

Keywords (Original Language):

Author NameUniversity of AuthorFaculty of Author
Abstract (2. Language): 
This research examines methods for solving the p-median problem, which is an important type of the facility location problems and belongs to the class of NP hard problems. A swarm based meta-heuristic, the Particle Swarm Optimization (PSO) algorithm is applied for the solution of the p-median problem. The study concludes with presentation of results obtained from the application of the PSO algorithm to two of the widely used ORLIB and Galvao test problems. In addition, the results are compared to the solutions obtained from applications of other well-known heuristic and meta-heuristic methods to the same problems.
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Abstract (Original Language): 
Bu çalışmada kuruluş yeri seçim problemleri içinde önemli bir yere sahip olan p-medyan probleminin çözümü üzerinde durulmuştur. NP-zor kombinatoryal optimizasyon problemler kategorisine giren p-medyan probleminin çözümü için sürü zekası tabanlı bir meta sezgisel olan Parçacık Sürü Optimizasyonu (PSO) algoritması kullanılmıştır. Çalışmanın sonunda PSO algoritmasının yaygın olarak kullanılan iki farklı test problemine uygulanması ile elde edilen sonuçlar verilmiştir. Ayrıca elde edilen bu sonuçlar literatürdeki farklı sezgisel ve meta sezgisellerin aynı test problemlerine uygulanması ile elde edilen sonuçlarla karşılaştırılmıştır.
FULL TEXT (PDF): 
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  • 2
241-257
  • Turkish

REFERENCES

References: 

[1] R. Tavakkoli, E. Shayan, Facilities Layout Design by Genetic Algorithms. Computers and Industrial Engineering, 35, 3-4, 527-530 (1998).
[2] M. Jamshidi, Median Location Problem, in Facility Location: Concepts, Models, Algorithms and Case Studies (R.Z. Farahani and M. Hekmatfar, Eds.), Physica-Verlag Heidelberg, 2009, p.177-191.
[3] S.L. Hakimi, Optimum Location of Switching Centers and the Absolute Centers and Medians of a Graph. Operations Research, 12, 450–459 (1964).
[4] M.S. Daskin, Network and Discrete Location: Models, Algorithms and Applications. John Wiley & Sons, Inc., New York, 1995, p.92-303.
[5] J. Current, M.S. Daskin and D. Schilling, Discrete Network Location Model, in Facility Location: Applications and Theory (Z. Drezner and H.W. Hamacher, Eds.), Springer-Verlag, 2001, p.83-120.
[6] D.R. Sule, Logistics of Facility Location and Allocation. Marcel Dekker, New York, US, 2001, p.173-220
[7] O. Alp, E. Erkut, Z. Drezner, An Efficient Genetic Algorithm for the p-Median Problem. Annals of Operations Research, 122, 1-4, 21-42 (2004).
[8] A.A. Kuehn, M.J. Hamburger, A Heuristic Program for Locating Warehouses. Management Science, 9, 4, 643-666 (1963).
[9] A. Manne, Plant Location Under Economies of Scale Decentralization and computation. Management Science, 11, 213-235 (1964).
[10] M. Balinski, Integer Programming, Methods, Uses and Computation. Management Science, 12, 253–313 (1965).
[11] S.L. Hakimi, Optimum Distribution of Switching Centers in a Communication Network and Some Related Graph Theoretic Problems. Operations Research, 13, 462–475 (1965).
[12] W. Pullan, A Population Based Hybrid Metaheuristic for the p-median Problem. IEEE Congress on Evolutionary Computation, 76-82 (2008).
[13] T. Küçükdeniz, Sürü Zekası Optimizasyon Tekniği ve Tedarik Zinciri Yönetiminde Bir Uygulama. Yayımlanmamış Doktora Tezi, İstanbul Üniversitesi, Fen Bilimleri Enstitüsü, Endüstri Mühendisliği Anabilim Dalı, (2009).
[14] G. Cornuejols, M.L. Fisher, G.L. Nemhauser, Location of Bank Accounts to Optimise Float: an Analytic Study of Exact and Approximate Algorithms. Management Science, 23, 789–810 (1977).
[15] O. Kariv, S.L. Hakimi, An Algorithmic Approach to Network Location Problems. II: The p-medians. SIAM Journal on Applied Mathematics, 37, 3, 539–560 (1979).
[16] C. ReVelle, R. Swain, Central Facilities Location. Geographical Analysis, 2, 30–42 (1970).
[17] J. Kennedy, R.C. Eberhart, Particle swarm optimization. Proceedings of IEEE International Conference on Neural Networks, Piscataway, NJ, USA, 1942-1948 (1995).
[18] J. Kennedy, R.C. Eberhart, A Discrete Binary Version of the Particle Swarm Optimization. Proceedings of the Conference on Systems Man and Cybernetics SMC97, 4104-4109 (1997).
N. Özçakar, M. Bastı / İstanbul Üniversitesi İşletme Fakültesi Dergisi 41, 2, (2012) 241-257 © 2012
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[19] Y. Shi, R.C. Eberhart, A Modified Particle Swarm Optimizer. Proceedings of the 1998 IEEE International Conference on Evolutionary Computation, IEEE Press, Piscataway, NJ, 1998, p. 69-73.
[20] Y. Shi, R.C. Eberhart, Parameter Selection in Particle Swarm Optimization. Evolutionary Programming VII: Proc. EP 98, Springer-Verlag, New York, 1998, p.591-600.
[21] J. Kennedy, R.C. Eberhart, Y. Shi, Swarm Intelligence. Morgan Kaufmann Publishers, San Francisco, USA, 2001, p. 287-323.
[22] M. Şevkli, M. Yenisey, Atölye Tipi Çizelgeleme Problemleri İçin Parçacık Sürü Optimizasyonu Yöntemi. İTÜ Dergisi, 5, 2, 58-68 (2006).
[23] R.C. Eberhart, Y. Shi, Particle Swarm Optimization: Developments, Applications and Resources. Proceedings on Evolutionary Computation Congress, Seoul, South Korea, 81-86 (2001).
[24] M.F. Taşgetiren, Y.C. Liang, M. Şevkli, G. Gençyılmaz, A Particle Swarm Optimization Algorithm for Makespan and Total Flowtime Minimization in The Permutation Flowshop Sequencing Problem. European Journal of Operational Research, 177, 3, 1930-1947 (2007).
[25] M. Şevkli, A.R. Güner, A Continuous Particle Swarm Optimization Algorithm for Uncapacitated Facility Location Problem. in Ant Colony Optimization and Swarm Intelligence (M. Dorigo et.al. Eds.), Springer-Verlag Berlin Heidelberg, Vol. 4150, 2006, p.316-323.
[26] J.E. Beasley, A Note on Solving Large p-Median Problems. European Journal of Operational Research, 21, 270-273 (1985).
[27] R.D. Galvão, C. ReVelle, A Lagrangean Heuristic for the Maximal Covering Location Problem. European Journal of Operations Research, 88, 114–123 (1996).
[28] F. Chiyoshi, R.D. Galvão, A Statistical Analysis of Simulated Annealing Applied to the p-Median Problem. Annals of Operations Research, 96, 61–74 (2000).
[29] K.E. Rosing, C.S. ReVelle, D.A. Schilling, A Gamma Heuristic for the p-Median Problem. European Journal of Operational Research, 117, 522–532 (1999).
[30] M. Maroszekz, C. Rettig, A Tabu Search for the p-Median Problem. Technical Report, Institute of Information Systems, School of Business, University of Hamburg, (2008).

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