A Decision Making Method via TOPSIS on Soft Sets

Yıl 2015, Cilt: 4 Sayı: 8, 57 - 70, 29.05.2015

Selim Eraslan

Öz

In this paper, we first present TOPSIS (techniquefor order performance by similarity to ideal solution) that is amulti-criteria decision making (MCDM) technique. TOPSIS is apractical and useful technique for ranking and selection of a number of externally determined alternatives through distance measures. We then give a decision making method by suing TOPSISon soft set theory. Finally an application is given for this newmethod

Anahtar Kelimeler

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Kaynakça

• Agrawal, V.P., Kohli, V. and Gupta, S., Computer aided robot selection: The
• multiple attribute decision making approach. International Journal of Production
• Research, 29(8), (1991) 1629-1644.
• Ali, M.I., Feng, F., Liu, X., Min, W.K. and Shabir, M., On some new operations
• in soft set theory, Comput. Math. Appl., 57, (2009) 1547-1553.
• Atanassov, K., Intuitionistic fuzzy sets, Fuzzy Sets and Systems, 20, (1986) 87-96.
• Belenson, S.M. and Kapur, K.C., An algorithm for solving multicriterion linear pro
• gramming problems with examples, Operational Research Quarterly, 24(1), (1973) 65-77.
• C¸ a˘gman, N., C¸ ıtak, F. and Engino˘glu, S., Fuzzy parameterized fuzzy soft set theory
• and its applications, Turkish Journal of Fuzzy Systems, 1(1), (2010) 21-35.
• C¸ a˘gman, N., C¸ ıtak, F. and Engino˘glu, S., FP-Soft set theory and its applications,
• Annals of Fazzy Mathematics and Informatics, 2(2), (2011) 219-226.
• C¸ a˘gman, N. and Engino˘glu, S., Soft set theory and uni-int decision making, Euro
• pean Journal of Operational Research, 207, (2010) 848-855.
• C¸ a˘gman, N. and Engino˘glu, S., Soft matrix theory and its decision makings. Com
• puters and Mathematics with Applications, 59, (2010) 3308-3314.
• C¸ a˘gman, N., Engino˘glu, S. and C¸ ıtak, F., Fuzzy soft set theory and its applications,
• Iranian Journal of Fuzzy Systems, 8 (3), (2011) 137-147.
• C¸ a˘gman, N. and Engino˘glu, S., Fuzzy Soft Matrix Theory and Its Applications in Decision Making, Iranian Journal of Fuzzy Systems, 9(1), (2012) 109-119.
• C¸ a˘gman, N., Contributions to the theory of soft sets, Journal of New Results in Science, 4, (2014) 33-41.
• Chen, M.F. and Tzeng, G.H., Combining gray relation and TOPSIS concepts for selecting an expatriate host country, Mathematical and Computer Modelling 40, (2004) 1473-1490.
• Deng, H., Yeh, C.H. and Willis, R. J., Inter-company comparison using modi- fied TOPSIS with objective weights. Computers and Operations Research, 27(10), (2000) 963-973.
• Feng, C.M. and Wang, R-T., Considering the financial ratios on the performance evaluation of highway bus industry. Transport Reviews, 21(4), (2001) 449-467.
• Hwang, C.L. and Yoon, K., Multiple attribute decision making: Methods and applications. New York: Springer-Verlag, (1981).
• Janic, M., Multicriteria evaluation of high-speed rail, transrapid maglev, and air passenger transport in Europe, Transportation Planning and Technology 26(6), (2003) 491-512.
• Kahraman, C., Engin, O., Kabak, O. and Kaya, I., Information systems outsourc- ing decisions using a group decision-making approach. Engineering Applications of Artificial Intelligence, 22(6), (2009) 832-841.
• Kim, G., Park, C.S. and Yoon, K.P., Identifying investment opportunities for advanced manufacturing systems with comparative-integrated performance mea- surement, International Journal of Production Economics 50, (1997) 23-33.
• Kwong, C.K. and Tam, S.M., Case-based reasoning approach to concurrent design of low power transformers, Journal of Materials Processing Technology 128, (2002) 136-141.
• Lai, Y.J., Liu, T.Y. and Hwang, C. L., TOPSIS for MODM. European Journal of Operational Research, 76(3), (1994) 486-500.
• Maji, P.K., Biswas, R. and Roy, A.R., Soft set theory, Computers and Mathematics with Applications, 45, (2003) 555-562.
• Milani, A.S., Shanian, A. and Madoliat, R., The effect of normalization norms in multiple attribute decision making models: A case study in gear material selection, Structural Multidisciplinary Optimization 29(4), (2005) 312-318.
• Molodtsov, D.A., Soft set theory-first results, Computers and Mathematics with Applications, 37(1), (1999) 19-31.
• Molodtsov, D.A., Leonov, V.Y. and Kovkov, D.V., Soft Sets Technique and Its Application, Nechetkie Sistemy i Myagkie Vychisleniya 1/1, (2006) 8-39.
• Opricovic, S. and Tzeng, G.H., ”Compromise Solution By MCDM Methods: A Comparative Analysis Of VIKOR and TOPSIS”, European Journal Of Operational Research, C:CLVI, (2004) 445-455.
• Parkan, C. and Wu, M.L., Decision-making and performance measurement models with applications to robot selection. Computers and Industrial Engineering, 36(3), (1999) 503-523.
• Pawlak, Z., Rough sets, International Journal of Information and Computer Sci- ences, 11, (1982) 341-356.
• Paxkan, C. and Wu, M.L., On the equivalence of operational performance measure- ment and multiple attribute decision making. International Journal of Production Research, 35(11), (1997) 2963-2988.
• Peters, M.L. and Zelewski, S., TOPSIS als Technik zur Effieienzanalyse, Zeitschrift f¨ur Ausbildung und Hochschulkontakt, (2007) 1-9.
• Rao, R.V., Evaluation of environmentally conscious manufacturing programs us- ing multiple attribute decision-making methods, Proceedings of the Institution of Mechanical Engineers-Part B-Engineering Manufacture, 222(3), (2008) 441-451.
• Ren, L., Zhang, Y., Wang, Y. and Sun, Z., Comparative analysis of a novel MTOPSIS method and TOPSIS. Applied Mathematics Research Express, 10. doi:10.1093/amrx/abm005. Article ID abm005, (2007)
• Shih, H.S., Lin, W.Y. and Lee, E.S., Group decision making for TOPSIS, in: Joint 9th IFSA World Congress and 20th NAFIPS International Conference, IFSA/NAFIPS, Vancouver, Canada, (2001) 2712-2717.
• Shih, H.S., Shyur, H.J. and Lee, E.S., An extension of TOPSIS for group decision making, Mathematical and Computer Modelling 45, (2007) 801-813.
• Shyura, H.J. and Shih, H.S., A hybrid MCDM model for strategic vendor selection. Mathematical and Computer Modelling, 44(7-8), (2006) 749-761.
• Srdjevic, B., Medeiros, Y.D.P. and Faria, A.S., An objective multi-criteria eval- uation of water management scenarios, Water Resources Management 18, (2004) 35-54.
• Stern, Z.S., Mehrez, A. and Hadad, Y., An AHP/DEA methodology for ranking decision making units, Intl. Trans. In Op. Res., 7, (2000) 109-124.
• Triantaphyllou, E., Multi-Criteria Decision Making Methods: A Comparative Study, Kluwer Academic Publishers, Netherlands, (2000), 139-140.
• Yang, T. and Chou, P. Solving a multiresponse simulation-optimization problem with discrete variables using a multi-attribute decision-making method, Mathe- matics and Computers in Simulation 68, (2005) 9-21.
• Yoon, K. and Hwang, C.L., Manufacturing plant location analysis by multiple attribute decision making: Part I-single-plant strategy, International Journal of Production Research 23, (1985) 345-359.
• Yoon, K.P. and Hwang, C.L., Multiple Attribute Decision Making: An Introduc- tion, Sage Pub., Thousand Oaks, CA, (1995).
• Yurdakul, M. and ˙I¸c, Y.T., Development of a performance measurement model for manufacturing companies using the AHP and Topsis approaches, International Journal of Production Research, 43(21), (2005) 4609-4641.
• Zadeh, L.A., Fuzzy Sets, Information and Control, 8, (1965) 338-353.
• Zeleny, M., A concept of compromise solutions and the method of the displaced ideal. Computers and Operations Research, 1(3-4), (1974) 479-496.
• Zhu, P. and Wen, Q., Operations on Soft Sets Revisited, Journal of Applied Math- ematics, 1-7, (2013).