Multi-Criteria Location Problem

  • Masoud Hekmatfar
  • Maryam SteadieSeifi
Part of the Contributions to Management Science book series (MANAGEMENT SC.)


Decision-making is the process of selecting a possible subset of decisions from all the available alternatives (feasible space). We introduced many decision-making models including one objective function, so far. Almost there are many criteria for judging the optimality of decision. In this situation, we will be faced with the multi-criteria decision-making (MCDM).


Location Problem Facility Location Problem Fire Station Demand Point Facility Layout 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. Badri MA, Mortagy AK, Alsayed CA (1998) A multi-objective model for locating fire stations. Eur J Oper Res 110(2):243–260CrossRefGoogle Scholar
  2. Berman O, Drezner Z (2000) A note on the location of an obnoxious facility on a network. Eur J Oper Res 120:215–217CrossRefGoogle Scholar
  3. Berman O, Drezner Z, Wesolowsky G (2000) Routing and location on a network with hazardous threats. J Oper Res Soc 51:1093–1099Google Scholar
  4. Captivo ME, Climaco J, Figueira J, Martins E. Santos JL (2000) Solving multiple criteria knapsack problems using labeling algorithms. Paper presented at IO2000, SetubalGoogle Scholar
  5. Carrizosa E, Conde E, Fernandez FR, Puerto J (1993) Efficiency in Euclidean constrained location problems. Oper Res Lett 14(5):291–295CrossRefGoogle Scholar
  6. Chiang WC, Kouvelis P, Urban TL (2006) Single- and multi-objective facility layout with workflow interference considerations. Eur J Oper Res 174:1414–1426CrossRefGoogle Scholar
  7. Cohon JL (1978) Multiobjective programming and planning. In: Mathematics in science and engineering. vol 140 Academic, NYGoogle Scholar
  8. Curtin KM, Church RL (2003) A family of location models for multiple-type discrete dispersion. Geogr Anal 38:248–270CrossRefGoogle Scholar
  9. Deb K, Pratap A, Agarwal S, Meyarivan T (2002) A fast and elitist multi objective genetic algorithm. NSGA-II”, IEEE Trans Evol Comput 6(2):182–197Google Scholar
  10. Ehrgott M, Gandibleux X (2000) An annotated bibliography of multicriteria combinatorial optimization OR-Spectr 22(4) 425–460Google Scholar
  11. Eiselt HA, Laporte G (1995) Objectives in location problems, in facility location. In: Drezner Z (ed) A survey of application and methods Springer, NY, pp 151–180Google Scholar
  12. Erkut E, Neuman S (1989) Analytical models for locating undesirable facilities. Eur J Oper Res 40:275–291CrossRefGoogle Scholar
  13. Erkut E, Neuman S (1990) Comparison of four models for dispersing facilities. INFOR 29(2):68–86Google Scholar
  14. Erkut E, Neuman S (1992) A multi-objective model for locating undesirable facilities. Ann Oper Res 40:209–227CrossRefGoogle Scholar
  15. Fonseca CM, Fleming PJ (1993) Multi objective genetic algorithms. In: IEE colloquium on genetic algorithms for control systems engineering vol 130, London, MayGoogle Scholar
  16. Gandibleux X, Jaszkiewicz A, Freville A, Slowinski R (2000) Multiobjective metaheuristics J Heurist 6(3):291–431CrossRefGoogle Scholar
  17. Giannikos I (1998) A multi-objective programming model for locating treatment sites and routing hazardous wastes. Eur J Oper Res 104:333–342CrossRefGoogle Scholar
  18. Hajela P, Lin CY (1992) Genetic search strategies in multi criterion optimal design. Struct Optim 4(2):99–107CrossRefGoogle Scholar
  19. Hakimi SL (1964) Optimum locations of switching center and the absolute center and medians of a graph. Oper Res 12:450–459CrossRefGoogle Scholar
  20. Halpern J (1978) Finding minimal center median convex combination (centdian) of a graph. Manage Sci 24(5):535–544CrossRefGoogle Scholar
  21. Hamacher HW, Nickel S (1996) Multicriteria planar location problems. Eur J Oper Res 94:66–86CrossRefGoogle Scholar
  22. Hamacher HW, Labbe M, Nickel S (1998) Multicriteria network location problems with sum objective. Networks 33:79–92CrossRefGoogle Scholar
  23. Hamacher HW, Labbe M, Nickel S (2002) Multicriteria semi-obnoxious network location problems (MSNLP) with sum and center objectives. Ann Oper Res 110:33–53CrossRefGoogle Scholar
  24. Hansen P, Perreur J, Thisse JF (1980) Location theory, dominance and convexity: some further results. Oper Res 28:1241–1250CrossRefGoogle Scholar
  25. Hooker JN, Garfinkel RS, Chen CK (1991) Finite dominating sets for network location problems. Oper Res 39(1):100–118CrossRefGoogle Scholar
  26. Hwang CL, Lin ML (1987) Group decision-making under multiple criteria. Springer, New YorkCrossRefGoogle Scholar
  27. Hwang CL, Masud ASM (1979) Multiple objective decision-making. Springer, New YorkCrossRefGoogle Scholar
  28. Hwang CL, Yoon K (1981) Multiple attribute decision-making. Springer, New YorkCrossRefGoogle Scholar
  29. Klamroth K, Wiecek M (2000) Dynamic programming approach to the multiple criteria knapsack problem. Naval Res Logist 47:57–76CrossRefGoogle Scholar
  30. Klein D, Hannan E (1982) An algorithm for the multiple objective integer linear programming problem. Eur J Oper Res 9:378–385CrossRefGoogle Scholar
  31. Krarup J, Pruzan PM (1983) The simple plant location problem: survey and synthesis. Eur J Oper Res 12:36–81CrossRefGoogle Scholar
  32. Krarup J, Pisingera D, Plastriab F (2002) Discrete location problems with push–pull objectives. Discrete Appl Math 123:363–378CrossRefGoogle Scholar
  33. Lee SM, Green GI, Kim C (1981) A multiple criteria model for the location-allocation problem. Comput Oper Res 8:1–8CrossRefGoogle Scholar
  34. Lin CKY, Kwok RCW (2006) Multi-objective meta heuristics for a location-routing problem with multiple use of vehicles on real data and simulated data. Eur J Oper Res 175:1833–1849CrossRefGoogle Scholar
  35. Moreno JA (1985) A correction to the definition of local center. Eur J Oper Res 20:382–385CrossRefGoogle Scholar
  36. Murata T, Ishibuchi H (1995) MOGA: multi-objective genetic algorithms. In: Proceedings of the IEEE international conference on evolutionary computation, Perth, WA, IEEE, Australia, 29 November–1 DecemberGoogle Scholar
  37. Ogryczak W (1999) On the distribution approach to location problems. Comput Ind Eng 37:595–612CrossRefGoogle Scholar
  38. Pati RK, Vrat P, Kumar P (2008) A goal programming model for paper recycling system. Omega 36:405–417CrossRefGoogle Scholar
  39. Pelegrin B, Fernandez FR (1988) Determination of efficient points in multiple objective location problems. Naval Res Logist Quart 35:697–705CrossRefGoogle Scholar
  40. Perez-Brito D, Moreno-Perez JA, Rodriguez-Martin I (1998) The 2-facility centdian network problem. Location Sci 6:369–381CrossRefGoogle Scholar
  41. Puerto J, Fernandez FR (1999) Multicriteria mini-sum facility location problems. J Multicriteria Decision Anal 8:268–280CrossRefGoogle Scholar
  42. Rahman M, Kuby M (1995) A multi-objective model for locating solid-waste transfer facilities using an empirical opposition function. INFOR 33:34–49Google Scholar
  43. Rakas J, Teodorovic D, Kim T (2004) Multi-objective modeling for determining location of undesirable facilities. Transp Res Pt 9:125–138Google Scholar
  44. Ramesh R, Zionts S, Karwan M (1986) A class of practical interactive branch and bounds algorithms for multicriteria integer programming. Eur J Oper Res 26:161–172CrossRefGoogle Scholar
  45. Rasmussen LM (1986) Zero-one programming with multiple criteria. Eur J Oper Res 26:83–95CrossRefGoogle Scholar
  46. Ratick, White A (1988) A risk-sharing model for locating noxious facilities. Environ Plan 15:165–179CrossRefGoogle Scholar
  47. ReVelle C (2000) Research challenges in environmental management. Eur J Oper Res 121:218–231CrossRefGoogle Scholar
  48. Ross GT, Soland RM (1980) A multicriteria approach to location of public facilities. Eur J Oper Res 4:307–321CrossRefGoogle Scholar
  49. Schaffer JD (1985) Multiple objective optimization with vector evaluated genetic algorithms. In: Proceedings of the international conference on genetic algorithm and their applicationsGoogle Scholar
  50. Solanki R (1991) Generating the noninferior set in mixed biobjective linear programs: an application to a location problem. Comput Oper Res 18:1–15CrossRefGoogle Scholar
  51. Srinivas N, Deb K (1994) Multi objective optimization using non dominated sorting in genetic algorithms. J Evol Comput 2(3):221–48CrossRefGoogle Scholar
  52. Szidarovszky F, Gershon ME, Duchstein L (1986) Techniques for multi-objective decision-making in systems management. Elsevier, AmsterdamGoogle Scholar
  53. Tzeng GH, Chen YW (1999) The optimal location of airport fire stations: a fuzzy multi-objective programming and revised genetic algorithm approach. Transport Plan Technol 23:37–55CrossRefGoogle Scholar
  54. Ulungu EL, Teghem J (1994) Multi-objective combinatorial optimization problems: a survey. J Multi-criteria Decisions Anal 3:83–104CrossRefGoogle Scholar
  55. Villarreal B, Karwan MH (1981) Multicriteria integer programming: a (hybrid) dynamic programming recursive approach. Math Program 21:204–233CrossRefGoogle Scholar
  56. Wayman MM, Kuby M (1994) Proactive optimization: general framework and a case study using a toxic waste location model with technology choice. Paper presented at the international symposium on locational decisions, ISOLDE VI, Lesvos and Chios, GreeceGoogle Scholar
  57. Wendell RE, Hurter AP (1973) Location theory, dominance and convexity. Oper Res 21:314–320CrossRefGoogle Scholar
  58. Wendell RE, Hurter AP Jr, Lowe TJ (1977) Efficient points in location problems. AIIE Trans 9(3):238–246CrossRefGoogle Scholar
  59. Yang L, Jones BF, Yang SH (2007) A fuzzy multi-objective programming for optimization of fire station locations through genetic algorithms. Eur J Oper Res 181:903–915CrossRefGoogle Scholar
  60. Z.-Farahani R, Asgari N (2007) Combination of MCDM and covering techniques in a hierarchical model for facility location: a case study. Eur J Oper Res 176:1839–1858Google Scholar
  61. Zionts S (1979) A survey of multiple criteria integer programming methods. Ann Discrete Math 5:389–398CrossRefGoogle Scholar
  62. Zionts S, Wallenius J (1980) Identifying efficient vectors: some theory and computational results. Oper Res 23:785–793CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  1. 1.Department of Industrial EngineeringAmirkabir University of TechnologyTehranIran

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