CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

Developing Fuzzy TOPSIS Method based on Interval-valued Fuzzy Sets

by Yahia Zare Mehrjerdi
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 42 - Number 14
Year of Publication: 2012
Authors: Yahia Zare Mehrjerdi
10.5120/5759-7891

Yahia Zare Mehrjerdi . Developing Fuzzy TOPSIS Method based on Interval-valued Fuzzy Sets. International Journal of Computer Applications. 42, 14 ( March 2012), 7-18. DOI=10.5120/5759-7891

@article{ 10.5120/5759-7891,
author = { Yahia Zare Mehrjerdi },
title = { Developing Fuzzy TOPSIS Method based on Interval-valued Fuzzy Sets },
journal = { International Journal of Computer Applications },
issue_date = { March 2012 },
volume = { 42 },
number = { 14 },
month = { March },
year = { 2012 },
issn = { 0975-8887 },
pages = { 7-18 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume42/number14/5759-7891/ },
doi = { 10.5120/5759-7891 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:31:17.348598+05:30
%A Yahia Zare Mehrjerdi
%T Developing Fuzzy TOPSIS Method based on Interval-valued Fuzzy Sets
%J International Journal of Computer Applications
%@ 0975-8887
%V 42
%N 14
%P 7-18
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Ranking competing alternatives in terms of their overall performance with respect to some criterions in fuzzy environment is possible by the use of fuzzy TOPSIS methodology using interval-valued fuzzy-sets concepts. This author presents an effective fuzzy multi-criteria method based upon the fuzzy model and the concepts of positive ideal and negative ideal solution points for prioritizing alternatives using inputs from a team of decision makers. The fuzzy sets concepts are used to evaluate the performance of alternatives and the importance of criteria. Fuzzy TOPSIS based on the interval-valued fuzzy-sets is fully described and a case study on RFID comprised of four main criteria and five alternatives is constructed and solved by the proposed extended TOPSIS method. The TOPSIS methodology used in this article is able to grasp the ambiguity exists in the utilized information and the fuzziness appears in the human judgments and preferences. TOPSIS technique can easily produce satisfactory results, and hence stimulates creativity and the invention for developing new methods and alternative approaches. This article is a very useful source of information for Fuzzy TOPSIS based on the interval-valued fuzzy sets and extends the area of application of RFID technology in general. Due to the fact that a better management of a system is related to the full understanding of the technologies implemented and the system under consideration, sufficient background on the methodologies are provided and a case study is developed and solved by the proposed method.

References
  1. Chen, C. T. (2000). Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy Sets and Systems, 114, 1–9.
  2. Chen, C. T. , Lin, C. T. and Huang, S. F. (2006), "A fuzzy approach for supplier evaluation and selection in supply chain management", International Journal of Production Economics, Vol. 102 No. 2, pp. 289-301.
  3. Kuo, M. S. , Tzeng, G. H. , & Huang, W. C. (2007). Group decision-making based on concepts of ideal and anti-ideal points in a fuzzy environment. Mathematical and Computer Modeling, 45, 324–339.
  4. Hwang, C. L. and Yoon, K. (1981), Multiple Attribute Decision Making Methods and Applications, Springer, New York, NY.
  5. Chu, T. C. (2002), "Facility location selection using fuzzy TOPSIS under group decisions", international Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, Vol. 10 No. 6, pp. 687-701.
  6. Tzeng, G. ; Lin, C. ; Opricovic, S. , (2005). Multi-criteria analysis of alternative-fuel buses for public transportation, Energ. Policy, 33 (11), 1373-1383.
  7. Zanakis, S. H. , Solomon, A. , Wishart, N. and Dublish, S. (1998), "Multi-attribute decision making: a simulation comparison of select methods", European Journal of Operational Research, Vol. 107, pp. 507-29.
  8. Triantphyllou, E. , Lin, C. T. , Development and evaluation of five fuzzy multi attribute decision making methods, international journal of Approximate Resoning 14, 1996, 281-310.
  9. Bottani, E. and Rizzi, A. (2006), "A fuzzy TOPSIS methodology to support outsourcing of logistics services", Supply Chain Management: An International Journal, Vol. 11 No. 4, pp. 294-308.
  10. Grattan-Guinness, I. , Fuzzy membership mapped onto interval and many-valued quantities, 1975, 149-160.
  11. Gorzaczany, M. B. , A method of inference in approximate reasoning based on interval-valued fuzzy sets, Fuzzy Sets and Systems 21, 1987, 1-17.
  12. Turksen, L. B. , Interval valued strict preference with Zadeh triples, fuzzy sets and systems 78, 1996, 295-307.
  13. Wang, G. , Li, X. , The applications of interval-values fuzzy numbers and interval distribution numbers, fuzzy sets and systems 98, 1998, 331-335.
  14. Yen, J. , Langari, R. , Fuzzy Logic Intelligence, Control, and Information, Prentice Hall Publishing Company, 1999
  15. Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8, 338–353.
  16. Zadeh, L. A. , The concept of linguistic variable and its application to approximate reasoning, Inform. Science I: 8 (1975)199–249; II: 8 (1975) 310–357; III: 9 (1975) 43–80.
  17. Zadeh, L. A. , Fuzzy sets, usually and common-sense reasoning, in: L. M. Vaina (Ed. ), Matters of Intelligence, Reidel, Dordrecht, 1987, pp. 289–309.
  18. Herrera, F. , Lopez, E. , Menda˜na, C. , Rodriguez, M. , A linguistic decision model to suppliers selection in international purchasing, in: L. A. Zadeh, J. Kacprzyk (Eds. ), Computing with words in information=intelligent systems 2. Applications, Physica-Verlag, Schursberg, 1999, pp. 500–524.
  19. Herrera, F. , Herrera-Viedma, E. , Linguistic decision analysis: Steps for solving decision problems under linguistic information, Fuzzy Sets and Systems 115 (2000) 67–82.
  20. Kacprzyk, J. , Group decision making with a fuzzy linguistic majority, Fuzzy Sets and Systems (1986) 18, 105–118.
  21. Delgado, M. , Verdegay, J. L. , Vila, v, Linguistic decision making models, Int. J. Intel. Systems 7 (1993) 479–492.
  22. Dyer, J. S. , & Sarin, R. K. (1979). Measurable multi-attribute value functions. Operations Research, 39, 810–822.
  23. Bordogna, G. , Pasi, G. , A fuzzy linguistic approach generalizing Boolean information retrieval: a model and its evaluation, J. Amer. Soc. Inform. Systems 44 (1993) 70–82.
  24. Degani, R. , Bortolan, G. , The problem of linguistic approximation in clinical decision making. Int. J. Approximate Reasoning 2 (1988) 143–162.
  25. Law, C. K. , Using fuzzy numbers in educational grading system, Fuzzy Sets and Systems 83 (1996) 311–323
  26. Chen, S. J. , & Hwang, C. L. (1992). Fuzzy multiple attribute decision making. Berlin: Springer.
  27. Negi, D. S. (1989). Fuzzy analysis and optimization. PhD thesis. Department of Industrial Engineering, Kansas State University.
  28. Chen, M. F. , Tzeng, G. H. , & Ding, C. G. (2003). Fuzzy MCDM approach to select service provider. IEEE International Conference on Fuzzy Systems, 572–577.
  29. Liang, G. S. (1999). Fuzzy MCDM based on ideal and anti-ideal concepts. European Journal of Operational Research, 112, 682–691.
  30. Wang, Y. M. , and T. M. S. Elhag, Fuzzy TOPSIS method based on alpha level sets with an application to bridge risk assessment, Expert Systems with Applications 31 (2005), pp. 309–319.
  31. Wang, Y. J. , & Lee, H. S. (2007). Generalizing TOPSIS for fuzzy multiple-criteria group decision-making. Computers and Mathematics with Applications, 53, 1762–1772.
  32. Wang, Y. M. , Luo, Y. , & Hua, Z. S. (2007). A note on group decision-making based on concepts of ideal and anti-ideal points in a fuzzy environment. Mathematical and Computer Modeling, 46, 1256–1264.
  33. Yeh, C. H. , Deng, H. , Chang, Y. H. (2000). Fuzzy multi criteria analysis for performance evaluation of bus companies. European Journal of Operational Research, 126, 459–473.
  34. Yeh, C. H. , & Deng, H. (2004). A practical approach to fuzzy utilities comparison in fuzzy multi criteria analysis. International Journal of Approximate Reasoning, 35, 179–194.
  35. Kahraman, C. , Bu¨yu¨ko¨zkan, G. and Ates¸, N. Y. (2007a), "A two phase multi-attribute decision-making approach for new product introduction", Information Sciences, Vol. 177No. 7, pp. 1567-82.
  36. Kahraman, C. , Ates¸, N. Y. , C¸ evik, S. and Gu¨lbay, M. (2007b), "Fuzzy multi-attribute cost-benefit analysis of e-services", International Journal of Intelligent Systems, Vol. 22 No. 5, pp. 547-65.
  37. Kahraman, C. , C¸ evik, S. , Ates¸, N. Y. and Gu¨lbay, M. (2007c), "Fuzzy multi-criteria evaluation of industrial robotic systems", Computers & Industrial Engineering, Vol. 52 No. 4, pp. 414-33.
  38. Kahraman, C. , Ates¸, N. Y. , C¸ evik, S. , Gu¨lbay, M. and Erdog?an, S. A. (2007d), "Hierarchical fuzzy TOPSIS model for selection among logistics information technologies", Journal of Enterprise Information Management, Vol. 20 No. 2, pp. 143-68.
  39. Deng, H. , Yeh, C. H. , & Willis, R. J. (2000). Inter-company comparison using modified TOPSIS with objective weights. Computers and Operations Research, 27, 963–973.
  40. Chen, M. F. , and G. H. Tzeng, Combining grey relation and TOPSIS concepts for selecting an expatriate host country, Mathematical and Computer Modeling 40 (2004), pp. 1473–1490.
  41. Tsuar, S. H. , Chang, T. Y. , & Yen, C. H. (2002). Evaluation of airline service quality by fuzzy MCDM. Tourism Management, 23, 107–115.
  42. Yoon, K. and Hwang, C. L. (1985), "Manufacturing plant location analysis by multiple attribute decision making: Part I – single plant strategy", International Journal of Production Research, Vol. 23 No. 2, pp. 345-59.
  43. Parkan, C. and Wu, M. (1999), "Decision-making and performance measurement models with applications to robot selection", Computers & Industrial Engineering, Vol. 36 No. 3, pp. 503-23.
  44. Saremi, M. , S. Farid Mousavi, and Amir Sanayei (2008), TQM consultant selection in SME with TOPSIS under fuzzy environment, Expert Systems with Applications Vol. 36.
  45. Chu, T. C. , & Lin, Y. C. (2003). A fuzzy TOPSIS method for robot selection. International Journal of Manufacturing Technology, 21, 284–290.
  46. Abo-Sina, M. A. , & Amer, A. H. (2005). Extensions of TOPSIS for multi objective large-scale nonlinear programming problems. Applied Mathematics and Computation, 162, 243–256.
  47. Zhang, G. and Lu, J. (2003), "An integrated group decision-making method dealing with fuzzy preferences for alternatives and individual judgments for selection criteria", Group Decision and Negotiation, Vol. 12, pp. 501-15.
  48. Xanthopulos, Z. , E. Melachrinoudis and M. Solomon 2000. Interactive multi-objective group decision making with interval parameters, Management Science 46 (12).
  49. Sengupta, A. , and T. K. Pal, 2000. On comparing interval numbers, European Journal of Operational Research 127.
  50. Djellab, H. , and K. Djellab, Preemptive hybrid flowshop scheduling problem of interval orders, European Journal of Operational Research 137, (2002).
  51. Yoon, K. , The propagation of errors in multiple-attribute decision analysis: A practical approach, Journal of Operation Research Society 40 (7), (1989).
  52. Bryson, N. , and A. Mobolurin, An action learning evaluation procedure for multiple criteria making problem, European Journal of Operational Research 96, (1996).
  53. Gonzalez-Pachon, J. , M. I. Rodriguez-Galiano and C. Romero, Transitive approximation to pair-wise comparison matrices by using interval goal programming, The Journal of the Operational Research Society 54 (5), (2003).
  54. Huang, Y. F. , B. W. Baetz, G. H. Huang and L. Liu, Violation analysis for solid waste management systems: An interval fuzzy programming approach, Journal of Environmental Management 65 (4), (2002).
  55. Zhang, J. , and J. Lui, (2002), The study of decision making method to interval number multiple attribute decision making problem, Journal of Forecast 21.
  56. Chu, T-C. , and Lin, Y-C. , An Interval arithmetic based fuzzy TOPSIS model, Expert Systems with Applications 36, 2009, pp. 10870-10876.
  57. Ashtiani, B. , Haghighirad, F. , Makui, A. , and Montazer, G. A. , Extension of Fuzzy TOPSIS method based on interval-values fuzzy sets, Applied Soft Computing 9, 2009, 457-461.
  58. Kohout, L. J. , Bandler, W. , Fuzzy interval inference utilizing the checklist paradigm and BK-relational products, 1996, pp. 291-335.
  59. Turksen, L. B. , Interval valued fuzzy sets based on normal forms, fuzzy sets and systems 20, 1986, 191-210.
  60. Turksen, L. B. , Interval valued fuzzy sets and compensatory, fuzzy sets and systems 51, 1992,295-307.
  61. Reyes, P. M. , Gimenez Thomsen, C. , Frazier, G. V. 2006. RFID attractiveness in the US and Spanish Grocery chains: an exploratory study. CEMS Research Seminar Proceedings.
  62. Dutta, A. , Lee, H. L. and Whang, S. (2007), "RFID and operations management: technology, value and incentives", Production and Operations Management, Vol. 16 No. 5, pp. 646-55.
  63. Cannon, A. L. , Reyes, P. M. , Frazier, G. V. , Prater, E. L. , RFID in the contemporary supply chain: multiple perspectives on its benefits and risks, International journal of operations and production management, Vol. 28, 2008.
  64. Legg, G. 1994. RFID tags connect smart cars to smart highways, EDN 39 (26), 33-34.
  65. Naresh, A. L. , and Jahern, C. T. 1997. Communication and tracking for construction vehicles, Journal of Construction Engineering and Management, ASCE 123, 261-268.
  66. Labs, W. 1998. New scanners, RFID systems help manufacturers keep tracks of products in the marking. Instrumentation and Control Systems 71, pp. 80.
  67. Wang, L. C. , Y. C. Lin and P. H. Lin, Dynamic mobile RFID-based supply chain control and management system in construction, International Journal of Advanced Engineering Informatics-Special Issue on RFID Applications in Engineering (2006).
  68. Lin, D. , Barton, R. , Bi, H. , Freimer, M. 2006. Challenges in RFID enabled supply chain management. Quality Progress 39, pp. 23-28.
  69. Naim et al. 2002. "A supply chain diagnostic methodology—determining the vector of change", Computers and Industrial Engineering 43, pp. 135–157.
  70. Lee LS, Kirk DF, and Jeffery SS, 2007. Radio frequency identification (RFID) implementation in the service sector: a customer-facing diffusion model. International Journal of Production Economics
  71. Repo, P. , Kerttula, M. , Salmeta, M. , Huomo, H. 2005. Virtual product design case study: the Nokia RFID tag reader. IEEE Pervasive Computing 4, PP. 95-99.
  72. Ngai, E. W. T. , Suk, F. F. C. , and Lo, S. Y. Y. , Development of an RFID based Sushi management system: the case of a conveyor belt sushi restaurant", International journal of production control, 2007.
  73. Ngai, E. W. T. , T. C. E. Cheng, S. Au and K. H. Lai, 2007. Mobile commerce integrated with RFID technology in a container depot, Decision Support Systems 43, pp. 62–76.
  74. Wamba, S. F. , Lefebvre, L. A. , Bendavid, Y. , and Lefebvre, E. 2007. "Exploring the impact of RFID technology and the EPC network on mobile B2B ecommerce: a case study in the retail industry", International Journal of Production Control.
  75. Wamba, S. F. , Y. Bendavid, L. A. Lefebvre and E. Lefebvre. 2006. RFID technology and the EPC network as enablers of mobile business: a case study in a retail supply chain, International Journal of Networking and Virtual Organizations 3, pp. 450–462.
  76. Chow, H. K. H. , Choy, K. L. , and Lee, W. B. 2003. "A dynamic logistics process knowledge-based system – An RFID multi-agent approach", Knowledge based Systems 20, 2007, pp. 357-372.
  77. Estefania, A. , Stefano, Z. , and Santiago, M. , et al. 2007. "Flexible tag microlab development: gas sensors integration in RFID flexible tags for food logistics", Sensors and Actuators B, Chemical 127, pp. 2-7.
  78. Zare Mehrjerdi, Y. " Radio Frequency Identification: The big Player in the Healthcare Management", Journal of Health Organizations Management, Vol. 25 No. 5, 2011, pp. 490-505.
  79. Zare Mehrjerdi, Y. "RFID-enabled Healthcare Systems: Risks and Benefits Analysis", International Journal of Pharmaceutical and Healthcare Marketing, 2011.
  80. Zare Mehrjerdi, Y. Multi-Criteria Risk-Benefit Analysis of Healthcare Management, International Journal of Industrial Engineering & Production Research, March 2012, Vol. 23, pp. 23-33. ( to be appeared)
  81. Zare Mehrjerdi, Y. "RFID: The Big Player in the Libraries of the Future", The Electronic Library, Vol. 29 No. 1, 2011 pp. 36-51.
  82. Zare Mehrjerdi, Y. Library Expense Control: A System Dynamics Approach, The Electronic Library (to be appeared).
  83. Zare Mehrjerdi, Y. Hierarchical Multi-Criterion Risk-Benefit Analysis in Fuzzy Environment", Applied Soft Computing (to be appeared).
  84. Wismans, W. M. G. 1999. Identification and registration of animals In the European Union, Computers and Electronics in Agricultures 24, pp. 99-108.
  85. Cornelis, C. , Deschrjver, G. , Kerre, E. E. , Advances and challenges in interval-valued fuzzy logic. Fussy sets and systems 157, 2006, 622-627.
  86. Karnik, N. N. , and Mendel, J. M. , Operations on type-2 fuzzy sets, Fuzzy sets and systems 122, 2001, 327-348
  87. Shih, H. S. , Syur, H. J. , & Lee, E. S. (2007). An extension of TOPSIS for group decision making. Mathematical and Computer Modeling, 45, 801–813.
  88. Shyur, H. J. , & Shih, H. S. (2006). A hybrid MCDM model for strategic vendor selection. Mathematical and Computer Modeling, 44, 749–761.
Index Terms

Computer Science
Information Sciences

Keywords

Fuzzy Topsis Fuzzy Sets Interval-valued Fuzzy Sets System Selection Group Decision Making

Powered by PhDFocusTM