A new hybrid approach to discrete multiple facility location problem

Locating certain facilities in predetermined sites is named the multiple facility location problems (MFLP). The objective of these kinds of problems is locating facilities to serve a given set of customers so that candidate sites and requirements are known. When the new facility sites have to be selected from a given set of candidate sites, the mentioned location problem becomes a discrete multiple facility location problem (DMFLP). In this paper, a special approach of DMFLP is considered where different multiple facilities have to be placed (location decision) and also customers have to be assigned to these facilities (allocation or assignment). The mathematical model of the proposed problem is developed, and with respect to the complexity of solving the mathematical model, especially in large scale, a new hybrid approach is proposed based on tabu search algorithm to solve the problem at each scale. Computational results on several randomly generated problems in comparison with a new proposed lower bound obtained from Lagrangian relaxation indicate that the proposed hybrid approach is both accurate and efficient.

[1]  Seyed Reza Hejazi,et al.  Supply chain modeling in uncertain environment with bi-objective approach , 2009, Comput. Ind. Eng..

[2]  Dileep R. Sule,et al.  Manufacturing facilities : location, planning, and design , 1988 .

[3]  Peng Zhang,et al.  A new approximation algorithm for the k-facility location problem , 2006, Theor. Comput. Sci..

[4]  Claude Tadonki,et al.  Solving the p-Median Problem with a Semi-Lagrangian Relaxation , 2006, Comput. Optim. Appl..

[5]  Adi Ben-Israel,et al.  A heuristic method for large-scale multi-facility location problems , 2004, Comput. Oper. Res..

[6]  Pierre Hansen,et al.  Variable Neighborhood Decomposition Search , 1998, J. Heuristics.

[7]  D. Shishebori,et al.  An efficient approach to discrete Multiple Different Facility Location Problem , 2008, 2008 IEEE International Conference on Service Operations and Logistics, and Informatics.

[8]  Minghe Sun Solving the uncapacitated facility location problem using tabu search , 2006, Comput. Oper. Res..

[9]  Fernando Y. Chiyoshi,et al.  A statistical analysis of simulated annealing applied to the p-median problem , 2000, Ann. Oper. Res..

[10]  T. Cheung,et al.  A new heuristic approach for the P-median problem , 1997 .

[11]  Horst A. Eiselt,et al.  A bibliography for some fundamental problem categories in discrete location science , 2008, Eur. J. Oper. Res..

[12]  Leon F. McGinnis,et al.  Facility Layout and Location: An Analytical Approach , 1991 .

[13]  Michelle R. Hribar,et al.  A dynamic programming heuristic for the P-median problem , 1997 .

[14]  Cem Iyigun,et al.  A generalized Weiszfeld method for the multi-facility location problem , 2010, Oper. Res. Lett..

[15]  J. Current,et al.  An efficient tabu search procedure for the p-Median Problem , 1997 .

[16]  Nicos Christofides,et al.  A tree search algorithm for the p-median problem , 1982 .

[17]  Marshall L. Fisher,et al.  An Applications Oriented Guide to Lagrangian Relaxation , 1985 .

[18]  Mark S. Daskin,et al.  Network and Discrete Location: Models, Algorithms and Applications , 1995 .

[19]  Ali Husseinzadeh Kashan,et al.  A mixed integer linear program and tabu search approach for the complementary edge covering problem , 2010, Adv. Eng. Softw..

[20]  Lou Y. Liang,et al.  The strategies of tabu search technique for facility layout optimization , 2008 .

[21]  Said Salhi,et al.  Facility Location: A Survey of Applications and Methods , 1996 .

[22]  Basheer M. Khumawala,et al.  An empirical comparison of tabu search, simulated annealing, and genetic algorithms for facilities location problems , 1997 .

[23]  Russell C. Eberhart,et al.  Recent advances in particle swarm , 2004, Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753).

[24]  M. John Hodgson,et al.  Heuristic concentration for the p-median: an example demonstrating how and why it works , 2002, Comput. Oper. Res..

[25]  Arthur M. Geoffrion,et al.  Lagrangian Relaxation for Integer Programming , 2010, 50 Years of Integer Programming.

[26]  Pasquale Avella,et al.  Logical reduction tests for the p‐problem , 1999, Ann. Oper. Res..

[27]  M. Jabalameli,et al.  Hybrid algorithms for the uncapacitated continuous location-allocation problem , 2008 .

[28]  Claude Lemaréchal,et al.  A geometric study of duality gaps, with applications , 2001, Math. Program..

[29]  Saïd Salhi,et al.  Defining tabu list size and aspiration criterion within tabu search methods , 2002, Comput. Oper. Res..

[30]  Charles S. Revelle,et al.  A gamma heuristic for the p-median problem , 1999, Eur. J. Oper. Res..

[31]  J. W. Gavett,et al.  The Optimal Assignment of Facilities to Locations by Branch and Bound , 1966, Oper. Res..

[32]  W. Domschke,et al.  Location and layout planning , 1997 .

[33]  Fred W. Glover,et al.  A user's guide to tabu search , 1993, Ann. Oper. Res..

[34]  Pascal Van Hentenryck,et al.  A simple tabu search for warehouse location , 2004, Eur. J. Oper. Res..

[35]  Russell C. Eberhart,et al.  A new optimizer using particle swarm theory , 1995, MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science.

[36]  Dominique Peeters,et al.  A comparison of two dual-based procedures for solving the p-median problem , 1985 .