Abstract
In this study, a new algorithm to solve uncapacitated facility location problems is proposed. The algorithm is a special version of original fuzzy c-means (FCM) algorithm. In FCM algorithm, unlabeled data are clustered and the cluster centers are determined according to priori known stopping criterion iteratively. Unlike the original FCM, the proposed algorithm allows the unlabeled data are to be assigned with single iteration to related clusters centers, which are assumed to be fixed and known a priori like location of facilities according to their degrees of membership. First, the proposed algorithm is applied to various benchmark problems from literature and compared with integer programming. Second, the proposed algorithm is tested and compared with particle swarm optimization (PSO) and artificial bee colony optimization (ABC) algorithms based uncapacitated facility location method on alternative versions such as discrete, continuous, discrete with local search and continuous with local search in literature for a Turkish fertilizer producer’s real data. Numerical results obtained from real life application show that the proposed algorithm outperforms the PSO-based and ABC-based algorithms.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Ayoub, N., Martins, R., Wang, K., Seki, H., Naka, Y.: Two levels decision system for efficient planning and implementation of bioenergy production. Energy Convers. Manag. 48, 709–723 (2007)
Balasko B., Abonyi J., Feil B.: Fuzzy clustering and data analysis toolbox for use with MATLAB (2005)
Barcelo, J., Hallefjord, A., Fernandez, E., Jörnsten, K.: Lagrangean relaxation and constraint generation procedures for capacitated plant location problems with single sourcing. OR Spectrum 12(2), 79–88 (1990)
Bezdek, J.C.: Pattern recognition with fuzzy objective function algorithms. Plenum, New York (1981)
Bongartz, I., Calamai, P.H., Conn, A.R.: A projection method for lp norm location-allocation problems. Math. Program. 66(1), 283–312 (1994)
Chepoi, V., Dimitrescu, D.: Fuzzy clustering with structural constraints. Fuzzy Sets Syst. 105, 91–97 (1999)
Dohn, A., Christensen, S.G., Rousoe, D.M.: The p/q ACTIVE uncapacitated facility location problem: investigation of the solution space and an LP-fitting heuristic. Eur. J. Oper. Res. 180, 532–546 (2007)
Döring, C., Lesot, M., Kruse, R.: Data analysis with fuzzy clustering methods. Comput. Stat. Data Anal. 51, 192–214 (2006)
Erlenkotter, D.: A dual-based procedure for uncapacitated facility location. Oper. Res. 26, 992–1009 (1978)
Esnaf, S., Kucukdeniz, T.: A fuzzy clustering-based hybrid method for a multi-facility location problem. J. Intell. Manuf. 20(2), 259–265 (2009)
Esnaf, S., Kucukdeniz, T.: Solving uncapacitated planar multi-facility location problems by revised weighted fuzzy c-means clustering algorithm. J. Multiple Valued Logic and Soft Comput. 21(1–2), 147–164 (2013)
Ghosh, D.: Neighbourhood search heuristics for the uncapacitated facility location problem. Eur. J. Oper. Res. 150, 150–162 (2003)
Greistorfer, P., Rego, C.: A simple filter-and-fan approach to the facility location problem. Comput. Oper. Res. 33, 2590–2601 (2006)
Guner, A.R., Sevkli, M.: A discrete particle swarm optimization algorithm for uncapacitated facility location problem. J. Artif. Evol. Appl. 2008(861512), 259–265 (2008)
Hsieh, K., Tien, F.: Self-organizing feature maps for solving location-allocation problems with rectilinear distances. Comput. Oper. Res. 31, 1017–1031 (2004)
Hu, T., Sheu, J.: A fuzzy-based customer classification method for demand-responsive logistical distribution operations. Fuzzy Sets Syst. 139, 431–450 (2003)
Karaboga D.: An idea based on honeybee swarm for numerical optimization, Technical report TR06. Erciyes University, Engineering Faculty, Computer Engineering Department (2005)
Karaboga, D., Basturk, B.: On the performance of artificial bee colony (ABC) algorithm. Appl. Soft Comput. 8, 687–697 (2008)
Karaboga, D., Akay, B.: A comparative study of artificial bee colony algorithm. Appl. Math. Comput. 214, 108–132 (2009)
Kashan, M.H., Nahavandi, N., Kashan, A.H.: DisABC: a new artificial bee colony algorithm for binary optimization. Appl. Soft Comput. J. 12(1), 342–352 (2012)
Kenesei T., Balasko B., Abony J.: A MATLAB toolbox and its web based variant for fuzzy cluster analysis. In: Proceedings of the 7th International Symposium on Hungarian Researchers on Computational Intelligence, Budapest, Hungary, 24–25 Nov 2006
Khumawala, B.M.: An efficient branch and bound algorithm for the warehouse location problem. Manage. Sci. 18, 718–731 (1972)
Klose, A.: A branch and bound algorithm for an uncapacitated facility location problem with a side constraint. Int. Trans. Oper. Res. 5(2), 155–168 (1998)
Levin, Y., Ben-Israel, A.: A heuristic method for large-scale multi-facility location problems. Comput. Oper. Res. 31, 257–272 (2004)
Osman, I.H., Christofides, N.: Capacitated clustering problems by hybrid simulated annealing and tabu search. Int. Trans. Oper. Res. 1(3), 317–336 (1994)
Resende, M.G.C., Werneck, R.F.: A hybrid multi-start heuristic for the uncapacitated facility location problem. Eur. J. Oper. Res. 174, 54–68 (2006)
Sevkli M., Guner A.R.: A continuous particle swarm optimization algorithm for uncapacitated facility location problem, Ant Colony Optimization and Swarm Intelligence. Lecture Notes in Computer Science, vol. 4150, pp. 316–323. Springer, Berlin, (2006)
Sun, M.: Solving the uncapacitated facility location problem using tabu search. Comput. Oper. Res. 33, 2563–2589 (2006)
Taillard, É.D.: Heuristic methods for large centroid clustering problems. J. Heuristics 9(1), 51–73 (2003)
Wu, L., Zhang, X., Zhang, J.: Capacitated facility location problem with general setup cost. Comput. Oper. Res. 33, 1226–1241 (2006)
Xu, G., Xu, J.: An LP rounding algorithm for approximating uncapacitated facility location problem with penalties. Inf. Process. Lett. 94, 119–123 (2005)
Van Roy, T.J.: A cross decomposition algorithm for capacitated facility location. Oper. Res. 34(1), 145–163 (1986)
Zalik, K.R.: Fuzzy C-means clustering and facility location problems. In: Proceedings of the 10th IASTED Conference Artificial Intelligence and Soft Computing, Palma de Mallorca, Spain, 28–30 Aug 2006
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Esnaf, Ş., Küçükdeniz, T., Tunçbilek, N. (2014). Fuzzy C-Means Algorithm with Fixed Cluster Centers for Uncapacitated Facility Location Problems: Turkish Case Study. In: Kahraman, C., Öztayşi, B. (eds) Supply Chain Management Under Fuzziness. Studies in Fuzziness and Soft Computing, vol 313. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-53939-8_21
Download citation
DOI: https://doi.org/10.1007/978-3-642-53939-8_21
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-53938-1
Online ISBN: 978-3-642-53939-8
eBook Packages: EngineeringEngineering (R0)