Comparison of fuzzy AHP and fuzzy TOPSIS methods for facility location selection

ORIGINAL ARTICLE

Abstract

Facility location selection is a multi-criteria decision problem and has a strategic importance for many companies. The conventional methods for facility location selection are inadequate for dealing with the imprecise or vague nature of linguistic assessment. To overcome this difficulty, fuzzy multi-criteria decision-making methods are proposed. The aim of this study is to use fuzzy analytic hierarchy process (AHP) and the fuzzy technique for order preference by similarity to ideal solution (TOPSIS) methods for the selection of facility location. The proposed methods have been applied to a facility location selection problem of a textile company in Turkey. After determining the criteria that affect the facility location decisions, fuzzy AHP and fuzzy TOPSIS methods are applied to the problem and results are presented. The similarities and differences of two methods are also discussed.

Keywords

Facility location selection Fuzzy logic Multi-criteria decision-making Fuzzy AHP Fuzzy TOPSIS 

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References

  1. 1.
    Yang J, Lee H (1997) An AHP decision model for facility location selection. Facilities 15(9/10):241–254CrossRefGoogle Scholar
  2. 2.
    Stevenson WJ (1993) Production / operations management, 4th edn. Richard D. Irwin Inc., HomewoodGoogle Scholar
  3. 3.
    Krajewski LJ, Ritzman LP (1993) Operations management. Addison-Wesley, BostonGoogle Scholar
  4. 4.
    Kahraman C, Cebeci U, Ulukan Z (2003) Multi-criteria supplier selection using fuzzy AHP. Logist Inf Manag 16(6):382–394CrossRefGoogle Scholar
  5. 5.
    Liang GS (1999) Fuzzy MCDM based on ideal and anti-ideal concepts. Eur J Oper Res 112:682–691MATHCrossRefGoogle Scholar
  6. 6.
    Chu TC (2002) Selecting plant location via a fuzzy TOPSIS approach. Int J Adv Manuf Technol 20:859–864CrossRefGoogle Scholar
  7. 7.
    Yong D (2006) Plant location selection based on fuzzy TOPSIS. Int J Adv Manuf Technol 28:839–844CrossRefGoogle Scholar
  8. 8.
    Liang GS, Wang MJ (1991) A fuzzy multi-criteria decision making method for facility site selection. Int J Prod Res 29(11):2313–2330MATHCrossRefGoogle Scholar
  9. 9.
    Kahraman C, Ruan D, Doğan İ (2003) Fuzzy group decision making for facility location selection. Inf Sci 157:135–153MATHCrossRefGoogle Scholar
  10. 10.
    Chou SY, Chang YH, Shen CY (2007) A fuzzy simple additive weighting system under group decision-making for facility location selection with objective/ subjective attributes. Eur J Oper Res, accepted paper, DOI 10.1016/ j.ejor.2007.05.006
  11. 11.
    Ishii H, Lee YL, Yeh KY (2007) Fuzzy facility location problem with preference of candidate sites. Fuzzy Sets Syst, article in press, DOI 10.1016/j.fss.2007.04.022
  12. 12.
    Zadeh LA (1965) Fuzzy sets. Inf Control 8:338–353MATHCrossRefMathSciNetGoogle Scholar
  13. 13.
    Ertuğrul İ, Karakaşoğlu N (2006) Fuzzy TOPSIS method for academic member selection in engineering faculty. International Joint Conferences on Computer, Information, and Systems Sciences, and Engineering (CIS2E 06) December 4–14Google Scholar
  14. 14.
    Bojadziev G, Bojadziev M (1998) Fuzzy sets and fuzzy logic applications. World Scientific, SingaporeGoogle Scholar
  15. 15.
    Ertuğrul İ, Tuş A (2007) Interactive fuzzy linear programming and an application sample at a textile firm. Fuzzy Optim Decis Making 6:29–49MATHCrossRefGoogle Scholar
  16. 16.
    Zimmermann HJ (1992) Fuzzy set theory and its applications. Kluwer, BostonGoogle Scholar
  17. 17.
    Zadeh LA (1975) The concept of a linguistic variable and its application to approximate reasoning-I. Inf Sci 8:199–249CrossRefMathSciNetGoogle Scholar
  18. 18.
    Bellman RE, Zadeh LA (1977) Local and fuzzy logics. In: Dunn JM, Epstein G (eds) Modern uses of multiple-valued logic. Kluwer, Boston, pp 105–151, 158–165Google Scholar
  19. 19.
    Deng H (1999) Multicriteria analysis with fuzzy pair-wise comparison. Int J Approx Reason 21:215–231CrossRefGoogle Scholar
  20. 20.
    Chen CT (2000) Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy Sets Syst 114:1–9MATHCrossRefGoogle Scholar
  21. 21.
    Saaty TL (1980) The analytic hierarchy process. McGraw-Hill, New YorkMATHGoogle Scholar
  22. 22.
    Vaidya OS, Kumar S (2006) Analytic hierarchy process: an overview of applications. Eur J Oper Res 169:1–29MATHCrossRefMathSciNetGoogle Scholar
  23. 23.
    Wang TC, Chen YH (2007) Applying consistent fuzzy preference relations to partnership selection. Omega 35:384–388CrossRefGoogle Scholar
  24. 24.
    Van Laarhoven PJM, Pedrcyz W (1983) A fuzzy extension of Saaty’s priority theory. Fuzzy Sets Syst 11:229–241MATHCrossRefGoogle Scholar
  25. 25.
    Buckley JJ (1985) Fuzzy hierarchical analysis. Fuzzy Sets Syst 17:233–247MATHCrossRefMathSciNetGoogle Scholar
  26. 26.
    Chang DY (1996) Applications of the extent analysis method on fuzzy AHP. Eur J Oper Res 95:649–655MATHCrossRefGoogle Scholar
  27. 27.
    Zhu K, Jing Y, Chang D (1999) A discussion on extent analysis method and applications of fuzzy AHP. Eur J Oper Res 116:450–456MATHCrossRefGoogle Scholar
  28. 28.
    Leung L, Cao D (2000) On consistency and ranking of alternatives in fuzzy AHP. Eur J Oper Res 124:102–113MATHCrossRefGoogle Scholar
  29. 29.
    Chou TY, Liang GS (2001) Application of a fuzzy multi-criteria decision making model for shipping company performance evaluation. Marit Policy Manage 28(4):375–392CrossRefGoogle Scholar
  30. 30.
    Chang YH, Cheng CH, Wang TC (2003) Performance evaluation of international airports in the region of east Asia. Proceedings of Eastern Asia Society for Transportation Studies 4:213–230Google Scholar
  31. 31.
    Hsieh TY, Lu ST, Tzeng GH (2004) Fuzzy MCDM approach for planning and design tenders selection in public office buildings. Int J Proj Manag 22:573–584CrossRefGoogle Scholar
  32. 32.
    Mikhailov L, Tsvetinov P (2004) Evaluation of services using a fuzzy analytic hierarchy process. Applied Soft Computing 5:23–33CrossRefGoogle Scholar
  33. 33.
    Enea M, Piazza T (2004) Project selection by constrained fuzzy AHP. Fuzzy Optim Decis Making 3:39–62MATHCrossRefGoogle Scholar
  34. 34.
    Kahraman C, Cebeci U, Ruan D (2004) Multi-attribute comparison of catering service companies using fuzzy AHP: the case of Turkey. Int J Prod Econ 87:171–184CrossRefGoogle Scholar
  35. 35.
    Tang Y, Beynon MJ (2005) Application and development of a fuzzy analytic hierarchy process within a capital investment study. J Econ Manage 1(2):207–230Google Scholar
  36. 36.
    Tolga E, Demircan M, Kahraman C (2005) Operating system selection using fuzzy replacement analysis and analytic hierarchy process. Int J Prod Econ 97:89–117CrossRefGoogle Scholar
  37. 37.
    Tang LL, Kuo YC, Lee ES (2005) A multi-objective model for Taiwan notebook computer distribution problem. In: Lan YC (ed) Global integrated supply chain systems. Idea, Hershey, pp 171–182Google Scholar
  38. 38.
    Gu X, Zhu Q (2006) Fuzzy multi-attribute decision making method based on eigenvector of fuzzy attribute evaluation space. Decis Support Syst 41:400–410CrossRefGoogle Scholar
  39. 39.
    Tüysüz F, Kahraman C (2006) Project risk evaluation using a fuzzy analytic hierarchy process: an application to information technology projects. Int J Intell Syst 21:559–584MATHCrossRefGoogle Scholar
  40. 40.
    Ayağ Z, Özdemir RG (2006) A fuzzy AHP approach to evaluating machine tool alternatives. J Intell Manuf 17:179–190CrossRefGoogle Scholar
  41. 41.
    Haq AN, Kannan G (2006) Fuzzy analytical hierarchy process for evaluating and selecting a vendor in a supply chain model. Int J Adv Manuf Tech 29:826–835CrossRefGoogle Scholar
  42. 42.
    Huang CC, Chu PY, Chiang YH (2006) A fuzzy AHP application in government-sponsored R&D project selection. Omega The International Journal of Management Science, article in press, DOI 10.1016/j.omega.2006.05.003
  43. 43.
    Chan FTS, Kumar N (2007) Global supplier development considering risk factors using fuzzy extended AHP-based approach. Omega 35:417–431CrossRefGoogle Scholar
  44. 44.
    Lee AHI, Chen WC, Chang CJ (2008) A fuzzy AHP and BSC approach for evaluating performance of IT department in the manufacturing industry in Taiwan. Expert Syst Appl 34(1):96–107CrossRefMathSciNetGoogle Scholar
  45. 45.
    Hwang CL, Yoon K (1981) Multiple attributes decision making methods and applications. Springer, BerlinGoogle Scholar
  46. 46.
    Wang YM, Elhag TMS (2006) Fuzzy TOPSIS method based on alpha level sets with an application to bridge risk assessment. Expert Syst Appl 31:309–319CrossRefGoogle Scholar
  47. 47.
    Triantaphyllou E, Lin CT (1996) Development and evaluation of five fuzzy multiattribute decision-making methods. Int J Approx Reason 14:281–310MATHCrossRefGoogle Scholar
  48. 48.
    Tsaur SH, Chang TY, Yen CH (2002) The evaluation of airline service quality by fuzzy MCDM. Tour Manage 23:107–115CrossRefGoogle Scholar
  49. 49.
    Chu TC, Lin YC (2003) A fuzzy TOPSIS method for robot selection. Int J Adv Manuf Technol 21:284–290CrossRefGoogle Scholar
  50. 50.
    Abo-Sinna MA, Amer AH (2005) Extensions of TOPSIS for multi-objective large-scale nonlinear programming problems. Appl Math Comput 162:243–256MATHCrossRefMathSciNetGoogle Scholar
  51. 51.
    Saghafian S, Hejazi SR (2005) Multi-criteria group decision making using a modified fuzzy TOPSIS procedure. Proceedings of the International Conference on Computational Intelligence for Modeling, Control and Automation, and International Conference on Intelligent Agents, Web Technologies and Internet Commerce, IEEEGoogle Scholar
  52. 52.
    Jahanshahloo GR, Hosseinzadeh LF, Izadikhah M (2006) Extension of the TOPSIS method for decision-making problems with fuzzy data. Appl Math Comput 181:1544–1551MATHCrossRefGoogle Scholar
  53. 53.
    Chen CT, Lin CT, Huang SF (2006) A fuzzy approach for supplier evaluation and selection in supply chain management. Int J Prod Econ 102:289–301CrossRefGoogle Scholar
  54. 54.
    Bottani E, Rizzi A (2006) A fuzzy TOPSIS methodology to support outsourcing of logistics services. Supply Chain Manag 11(4):294–308CrossRefGoogle Scholar
  55. 55.
    Wang TC, Chang TH (2007) Application of TOPSIS in evaluating initial training aircraft under fuzzy environment. Expert Syst Appl 33(4):870–880CrossRefGoogle Scholar
  56. 56.
    Li DF (2007) Compromise ratio method for fuzzy multi-attribute group decision making. Applied Soft Computing 7(3):807–817CrossRefGoogle Scholar
  57. 57.
    Benitez JM, Martin JC, Roman C (2007) Using fuzzy number for measuring quality of service in the hotel industry. Tour Manage 28:544–555CrossRefGoogle Scholar
  58. 58.
    Yang T, Hung CC (2007) Multiple-attribute decision making methods for plant layout design problem. Robot Comput-Integr Manuf 23:126–137CrossRefGoogle Scholar
  59. 59.
    Wang YJ, Lee HS (2007) Generalizing TOPSIS for fuzzy multi-criteria group decision making. Comput Math Appl 53:1762–1772CrossRefMathSciNetGoogle Scholar
  60. 60.
    Chen H (2004) A research based on fuzzy AHP for multi-criteria supplier selection in supply chain. Master thesis, National Taiwan University of Science and Technology, Department of Industrial ManagementGoogle Scholar
  61. 61.
    Kahraman C, Ateş NY, Çevik S, Gülbay M, Erdoğan SA (2007) Hierarchical fuzzy TOPSIS model for selection among logistics information technologies. Journal of Enterprise Information Management 20(2):143–168CrossRefGoogle Scholar
  62. 62.
    Ertuğrul İ, Karakaşoğlu N (2006) The fuzzy analytic hierarchy process for supplier selection and an application in a textile company. Proceedings of 5th International Symposium on Intelligent Manufacturing Systems, pp 195–207Google Scholar

Copyright information

© Springer-Verlag London Limited 2007

Authors and Affiliations

  1. 1.Business Administration DepartmentPamukkale UniversityDenizliTurkey

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