Abstract
In this paper, fuzzy group decision making based on extension of TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method which was proposed by Chen (Fuzzy Sets Syst, 114:1–9, 2000) is adopted for facility location selection. In this method, the ratings of various alternatives versus various subjective criteria and the weights of all criteria are assessed in linguistic variables represented by fuzzy numbers. By fuzzy numbers, it has been tried to resolve the ambiguity of concepts that are associated with human being’s judgments. To determine the order of the alternatives, closeness coefficient is defined by calculating the distances to the fuzzy positive ideal solution (FPIS) and fuzzy negative ideal solution (FNIS). In Chen’s approach, the distance between two fuzzy numbers is calculated with vertex method. But in this study, different distance measurement methods are used and the results are compared. Finally the proposed method has been applied to a facility location selection problem of a textile company in Turkey.
Similar content being viewed by others
References
Abo-Sinna MA, Amer AH (2005) Extensions of TOPSIS for multi-objective large-scale nonlinear programming problems. Appl Math Comput 162: 243–256
Bellman RE, Zadeh LA (1977) Local and fuzzy logics. In: Dunn JM, Epstein G (eds) Modern uses of multiple-valued logic. Kluwer, pp 105–151 & 158–165
Benitez JM, Martin JC, Roman C (2007) Using fuzzy number for measuring quality of service in the hotel industry. Tour Manag 28: 544–555
Bojadziev G, Bojadziev M (1998) Fuzzy sets and fuzzy logic applications. World Scientific Publishing, Singapore
Bottani E, Rizzi A (2006) A fuzzy TOPSIS methodology to support outsourcing of logistics services. Supply Chain Manag Int J 11(4): 294–308
Bozdağ CE, Kahraman C, Ruan D (2003) Fuzzy group decision making for selection among computer integrated manufacturing systems. Comput Ind 51: 14–29
Chen CT (2000) Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy Sets Syst 114: 1–9
Chen CT, Lin CT, Huang SF (2006) A fuzzy approach for supplier evaluation and selection in supply chain management. Int J Prod Econ 102: 289–301
Chu TC (2002) Selecting plant location via a fuzzy TOPSIS approach. Int J Adv Manuf Technol 20: 859–864
Chu TC, Lin YC (2003) A fuzzy TOPSIS method for robot selection. Int J Adv Manuf Technol 21: 284–290
Ertuğrul İ, Karakaşoğlu N (2006a, Dec 4–14) Fuzzy TOPSIS method for academic member selection in engineering faculty. Paper presented at the international joint conferences on computer, information, and systems sciences, and engineering (CIS2E 06)
Ertuğrul İ, Karakaşoğlu N (2006b, May 29–31) The fuzzy analytic hierarchy process for supplier selection and an application in a textile company. Paper presented at the 5th international symposium on intelligent manufacturing systems “Agents and Virtual Worlds”
Ertuğrul İ, Tuş A (2007) Interactive fuzzy linear programming and an application sample at a textile firm. Fuzzy Optim Decis Mak 6: 29–49
Ertuğrul İ, Karakaşoğlu N (2008) Comparison of fuzzy AHP and fuzzy TOPSIS methods for facility location selection. Int J Adv Manuf Technol 39: 783–795
Hwang CL, Yoon K (1981) Multiple attributes decision making methods and applications. Springer, Berlin
Jahanshahloo GR, Hosseinzadeh LF, Izadikhah M (2006) Extension of the TOPSIS method for decision-making problems with fuzzy data. Appl Math Comput 181: 1544–1551
Kahraman C, Cebeci U, Ulukan Z (2003a) Multi-criteria supplier selection using fuzzy AHP. Logist Inf Manag 16(6): 382–394
Kahraman C, Ruan D, Doğan İ (2003b) Fuzzy group decision making for facility location selection. Inf Sci 157: 135–153
Krajewski LJ, Ritzman LP (1993) Operations management. Addison-Wesley, USA
Li DF (2006) Compromise ratio method for fuzzy multi-attribute group decision making. Appl Soft Comput (article in press)
Saghafian S, Hejazi SR (2005) Multi-criteria group decision making using a modified fuzzy TOPSIS procedure. In: Proceedings of the 2005 international conference on computational intelligence for modeling, control and automation, and international conference on intelligent agents, web technologies and internet commerce. IEEE
Stevenson WJ (1993) Production / operations Management. Irwin, USA
Triantaphyllou E, Lin CT (1996) Development and evaluation of five fuzzy multiattribute decision-making methods. Int J Approx Reason 14: 281–310
Tsaur SH, Chang TY, Yen CH (2002) The evaluation of airline service quality by fuzzy MCDM. Tour Manag 23: 107–115
Wang YM, Elhag TMS (2006) Fuzzy TOPSIS method based on alpha level sets with an application to bridge risk assessment. Expert Syst Appl 31: 309–319
Yong D (2006) Plant location selection based on fuzzy TOPSIS. Int J Adv Manuf Technol 28: 839–844
Zadeh LA (1965) Fuzzy sets. Inf Control 8: 338–353
Zadeh LA (1975) The concept of a linguistic variable and its application to approximate reasoning-I. Inf Sci 8: 199–249
Zimmermann HJ (1992) Fuzzy set theory—and its applications. Kluwer, Boston
Zhang G, Lu J (2003) An integrated group decision-making method dealing with fuzzy preferences for alternatives and individual judgments for selection criteria. Group Decis Negotiat 12: 501–515
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Ertuğrul, İ. Fuzzy Group Decision Making for the Selection of Facility Location. Group Decis Negot 20, 725–740 (2011). https://doi.org/10.1007/s10726-010-9219-1
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10726-010-9219-1