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A tabu search approach to the uncapacitated facility location problem

Author

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  • K.S. Al‐Sultan
  • M.A. Al‐Fawzan

Abstract

In this paper, the uncapacitated facility location problem is considered. A tabu searchalgorithm for solving this problem is proposed. The algorithm is tested on some standardtest problems taken from literature and its performance is compared with the known optimalsolutions. Computational results show that the proposed algorithm produces optimal solutionsfor all test problems, and that it is very efficient in terms of time compared to existingalgorithms in the literature. Copyright Kluwer Academic Publishers 1999

Suggested Citation

  • K.S. Al‐Sultan & M.A. Al‐Fawzan, 1999. "A tabu search approach to the uncapacitated facility location problem," Annals of Operations Research, Springer, vol. 86(0), pages 91-103, January.
    • Handle: RePEc:spr:annopr:v:86:y:1999:i:0:p:91-103:10.1023/a:1018956213524
    DOI: 10.1023/A:1018956213524
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    Cited by:

    1. Martínez-Salazar, Iris Abril & Molina, Julian & Ángel-Bello, Francisco & Gómez, Trinidad & Caballero, Rafael, 2014. "Solving a bi-objective Transportation Location Routing Problem by metaheuristic algorithms," European Journal of Operational Research, Elsevier, vol. 234(1), pages 25-36.
    2. Ghosh, Diptesh, 2003. "Neighborhood search heuristics for the uncapacitated facility location problem," European Journal of Operational Research, Elsevier, vol. 150(1), pages 150-162, October.
    3. Schweiger, Katharina & Sahamie, Ramin, 2013. "A hybrid Tabu Search approach for the design of a paper recycling network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 50(C), pages 98-119.
    4. Prodhon, Caroline, 2011. "A hybrid evolutionary algorithm for the periodic location-routing problem," European Journal of Operational Research, Elsevier, vol. 210(2), pages 204-212, April.
    5. Fathali Firoozi, 2008. "Boundary Distributions in Testing Inequality Hypotheses," Working Papers 0046, College of Business, University of Texas at San Antonio.
    6. Mina Husseinzadeh Kashan & Ali Husseinzadeh Kashan & Nasim Nahavandi, 2013. "A novel differential evolution algorithm for binary optimization," Computational Optimization and Applications, Springer, vol. 55(2), pages 481-513, June.
    7. Drexl, Michael & Schneider, Michael, 2015. "A survey of variants and extensions of the location-routing problem," European Journal of Operational Research, Elsevier, vol. 241(2), pages 283-308.
    8. Melo, M.T. & Nickel, S. & Saldanha-da-Gama, F., 2012. "A tabu search heuristic for redesigning a multi-echelon supply chain network over a planning horizon," International Journal of Production Economics, Elsevier, vol. 136(1), pages 218-230.
    9. Escobar, John Willmer & Linfati, Rodrigo & Baldoquin, Maria G. & Toth, Paolo, 2014. "A Granular Variable Tabu Neighborhood Search for the capacitated location-routing problem," Transportation Research Part B: Methodological, Elsevier, vol. 67(C), pages 344-356.
    10. Ting, Ching-Jung & Chen, Chia-Ho, 2013. "A multiple ant colony optimization algorithm for the capacitated location routing problem," International Journal of Production Economics, Elsevier, vol. 141(1), pages 34-44.
    11. Sumanta Basu & Ghosh, Diptesh, 2008. "A review of the Tabu Search Literature on Traveling Salesman Problems," IIMA Working Papers WP2008-10-01, Indian Institute of Management Ahmedabad, Research and Publication Department.
    12. Wasner, Michael & Zapfel, Gunther, 2004. "An integrated multi-depot hub-location vehicle routing model for network planning of parcel service," International Journal of Production Economics, Elsevier, vol. 90(3), pages 403-419, August.
    13. Dupont, Lionel, 2008. "Branch and bound algorithm for a facility location problem with concave site dependent costs," International Journal of Production Economics, Elsevier, vol. 112(1), pages 245-254, March.
    14. Lin, C.K.Y. & Kwok, R.C.W., 2006. "Multi-objective metaheuristics for a location-routing problem with multiple use of vehicles on real data and simulated data," European Journal of Operational Research, Elsevier, vol. 175(3), pages 1833-1849, December.
    15. Karaoglan, Ismail & Altiparmak, Fulya & Kara, Imdat & Dengiz, Berna, 2011. "A branch and cut algorithm for the location-routing problem with simultaneous pickup and delivery," European Journal of Operational Research, Elsevier, vol. 211(2), pages 318-332, June.
    16. Yi, Wei & Ozdamar, Linet, 2007. "A dynamic logistics coordination model for evacuation and support in disaster response activities," European Journal of Operational Research, Elsevier, vol. 179(3), pages 1177-1193, June.
    17. Prodhon, Caroline & Prins, Christian, 2014. "A survey of recent research on location-routing problems," European Journal of Operational Research, Elsevier, vol. 238(1), pages 1-17.
    18. Wang, Shaojun & Sarker, Bhaba R. & Mann, Lawrence & Triantaphyllou, Evangelos, 2004. "Resource planning and a depot location model for electric power restoration," European Journal of Operational Research, Elsevier, vol. 155(1), pages 22-43, May.
    19. Balakrishnan, Anantaram & Banciu, Mihai & Glowacka, Karolina & Mirchandani, Prakash, 2013. "Hierarchical approach for survivable network design," European Journal of Operational Research, Elsevier, vol. 225(2), pages 223-235.
    20. Drexl, M. & Schneider, M., 2014. "A Survey of the Standard Location-Routing Problem," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 65940, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    21. Ahn, Jaemyung & de Weck, Olivier & Geng, Yue & Klabjan, Diego, 2012. "Column generation based heuristics for a generalized location routing problem with profits arising in space exploration," European Journal of Operational Research, Elsevier, vol. 223(1), pages 47-59.

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