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Azadfallah, Mohammad
- Reducing the Gap between Two MADM Models
Abstract Views :251 |
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Authors
Affiliations
1 Industrial Management, Islamic Azad University, Science and Research Branch, Tehran, IR
1 Industrial Management, Islamic Azad University, Science and Research Branch, Tehran, IR
Source
National Journal of System and Information Technology, Vol 8, No 2 (2015), Pagination: 53-64Abstract
Several methods have been proposed for solving Multi-Attribute Decision-Making problems (MADM). A major criticism of MADM is that different techniques may yield different results when applied to the same problem. In this paper, we investigate the performance of two well-known MADM models: 1. AHP, and 2. TOPSIS. Although, there is no exact way to know which model gives the right answer. But, AHP was selected as the basis to which to compare the other methods, because it extremely popular in practice. Then, by changing the separation measures in TOPSIS model from P=2 (Euclidean distance) to another values (P≠2; i.e. 1.1, 1.2, etc., based on Birnbaum, 1998, p. 185), result are investigated.Keywords
MADM, AHP, TOPSIS, Separation Measures, Euclidean Distance.
References
- Alinezhad A. and A. Amini, (2011), "sensitivity analysis of Topsis technique: the results of changes in the weight of one attribute on the final ranking of alternatives", Journal of Optimization in Industrial Engineering 7 (2011), 23-28
- Birnbaum M. H. (1998), "Measurement, judgment and decision making", Academic Press.
- Gelderman J. and O. Rentz, (2000)," Bridging the gap between American and European MADM approaches", presented at the 51st meeting of the European working group "multi criteria aid for decisions" in Madrid, 30-31.03.2000.
- Hwang C. L. and K. Yoon, (1981), "multiple attribute decision making; methods and applications", Springer – Verlag.
- Lin et al., (2008)," multi attribute group decision making model under the condition of uncertain information", Automation in Construction 17(2008), 792-797.
- Mianabadi H. A. and A. Afshar, (2008)," Multi-attribute Decision-making to Rank Urban Water Supply Schemes", Ab va Fazelab, No. 66, 2008, 34-45, in Iran.
- Olson D. L., (2004),"comparison of weights in Topsis method", Mathematical and Computer Modeling, Pergamon.
- Pawar S. S. and D. S. Verma, (2013)," digital camera evaluation base on AHP and Topsis", International Journal of Engineering Research, No. 2, Issue No. 2, 51-53.
- Saaty T. L., (2000),"Fundamentals of decision making and priority theory", Vol. VI of the AHP series, RWS Publication.
- Sennaroglu B. and S. Sen, (2012), "Integrated AHP and Topsis approach for supplier selection", 2nd international conference manufacturing engineering and management, 2012, 19-22.
- Triantaphyllou E. and S. H. Mann, (1995)," using the Analytic Hierarchy Process for decision making in engineering applications: some challenges," International Journal of Industrial Engineering: application and practice, Vol. 2, No. 1, 35-44.
- Ustinovichius et al., (2007)," Application of a quantitative multiple criteria decision making (MCDM-1) approach to the analysis of investments in construction", Control and Cybernetics, Vol. 36 (2007), No.1.
- Voogd J. H., (1982)," multiple criteria evaluation for urban and regional planning", Research Project: Dutch national physical planning agency (RPD), Delft, Netherlands.
- Zanakis et al., (1998)," A simulation comparisons of select method", European Journal of Operational Research 107 (1998), 507-529.
- The Impacts of Aggregation Rules, Measurement Scale and Normalization Methods on Ranking of Alternatives in AHP
Abstract Views :216 |
PDF Views:2
Authors
Affiliations
1 Business Studies and Development Office, Saipa Yadak, IR
1 Business Studies and Development Office, Saipa Yadak, IR
Source
National Journal of System and Information Technology, Vol 10, No 1 (2017), Pagination: 1-22Abstract
In this paper we analyze the impacts of various aggregation rules (additive and multiplicative), normalization methods (Saaty, vector, weitendorf’s linear, juttler-Korth, nonlinear and logarithmic), and measurement scales (linear, power, geometric, logarithmic, ischolar_main square, inverse linear and balanced), on the results of the well-known and widely used methods of MADM:Analytic Hierarchy Process (AHP). A problem with a known answer is used to test different conditions. In general, this studies an experimentally reveals that the 'Conventional AHP' method is more or equal effective to others in solving the Multiple Attribute Decision making problems. Therefore, we more recommended using the 'Conventional AHP' in various areas of human activities.Keywords
Aggregation, Measurement Scale, Normalization Method, AHP.References
- Barzilai J., 2001, "Notes on the Analytic Hierarchy Process", proceedings of the NSF design and manufacturing research conference, Tampa, Florida, 1-6.
- Choo E.U. and W.C. Wedley,2008,"Comparing fundamentals of Additive and Multiplicative Aggregation in ratio scale multi criteria decision making", The open operational research journal,2,1-7.
- Forman E. and M. A. Selly, 2001, "Decision by Objectives" ,World Scientific Press.
- Ishizaka A. et al., 2011, "Influence of Aggregation and Measurement Scale on Ranking a compromise Alternative in AHP", journal of the operational research society,62(4),700-710.
- Islam R., 2002,"Modified Nominal Group Technique for group decision making", IIUM journal of Economic and Management 10, No.2, 1-27.
- Islam R. and A. Nur Anisah, 2006,"Management Decision Making by the AHP: A proposed Modification for Large Scale problems", journal international Business and Entrepreneurship development", Vol.3.No.1/2,18-39.
- Luce R.D., 1997,"Quantification and Symmetry", British journal of Psychology, 88,395-398.
- Lootsma F.A., 1993,"context related scaling of human judgment in the Multiplicative AHP, SMART, and ELECTRE", IIASA, A 2361 - Luxemburg-Austria.
- Macharis C. et al. ,2004 , "Promethee and AHP”, European journal of operational research, 153,307-317.
- Maleki H. and A. Hassan Zadeh, 2012,” comparison of the REMBRANDET system with the Wnng and Elhag approach: a practical example of the rank reversal problem”, African journal of Business Management, Vol. 6(1), 459-473, 2012.
- Pavl D.M., 2000, "Normalization of attribute values in MADM violates the conditions of consistent choice IV, DI and α ", Yugoslav journal of operations research, 1,109-122.
- Ramanathan R. ,2001,"A note to the use of the AHP for environmental impact assessment”, journal of Environmental Management, 63, 27-35.
- Saaty T. L. , 2000,"Fundementals of decision making and priority theory", Vol. VI of the AHP series, RWS Publication.
- Saaty T. L. , 2001,"Decision making with dependence and feedback", Vol. IX of the AHP series, RWS Publication.
- Saaty T. L. , 2003 ,"Rank, normalization and idealization in the Analytic Hierarchy Process", ISAHP2003, Bali, Indonesia, August 7-9, 2003.
- Saaty T. L. , 2008,"relative measurement and its generalization in decision making", Rev. R. Acad. Scien. Serie A. Mat. Vol. 102(2), 2008, 251-318.
- Saaty T. L. , L. Vargas and R. Whitaker, 2009, "Addressing with brevity criticisms of the Analytic Hierarchy Process”, International journal of the Analytic Hierarchy Process, Vol. 1, Issue 1, 121-134.
- Sato Y.,2001,"The impact on scaling on the pair wise comparison of the Analytic Hierarchy Process, ISAHP,Berne,Switzerland,421-430.
- Srdjevic et al. (2014), first-level transitivity rule method for filling in incomplete pairwise comparison matrices in the Analytic Hierarchy Process, Appl. Math. Inf. Sci. 8, No. 2, 459-467.
- Stevens S. S. , 1946 ,"On the theory of scales of measurement", SCIENCE, 103, No.2684, 677-680.
- Triantaphyllou E. and K. Baig, 2005,"The impact of Aggregating Benefit and Cost criteria in four MCDA methods".IEEE Transactions on Engineering Management, 52,213-226.
- Turskis Z. et al. , 2009 ,"Multi Criteria optimization system for decision making in construction design and management", Engineering Economics, No.1 (61), 1-17.
- Wang X. and E. Triantaphyllou,2006,"Ranking irregularities when evaluating Alternatives by using some Multi Criteria Decision Analysis Methods", Handbook of Industrial and systems Engineering, CRC Press, Taylor & Francis Group , Boca Raton,FL,USA, chapter 27,1-12.
- Wang X., 2008,”A study of regret and rejoicing and a new MCDM method based on them”, doctorate thesis, Louisiana state university, USA.
- Wedley W.C., 2001,"AHP answers to problems with known composite values", ISAHP, Berne, Switzerland, 551-560.
- Wedley W.C. and E.U. Choo, 2003,"Muddled Magnitudes", ISAHP, Bali, Indonesia, 511-519.
- Wedley W.C. and E.U. Choo ,2008 ,"An analysis of AHP comparisons and priorities", ASAC, Halifax, Nova Scotia, 16-28.
- Zavadskas E.K. and Z. Turskis, 2008"A new Logarithmic Normalization method in Game theory", Informatica 19, No.2, 303-314.
- Zavadskas E.K. et al., 2010,"Attributes weights determining peculiarities in Multiple Attribute Decision Making methods", Engineering Economics, 21(1), 32-43.
- Influence of the Different Measurement Scale and Normalization Method on Results in Topsis
Abstract Views :213 |
PDF Views:4
Authors
Affiliations
1 Business Studies and Development Office, Saipa Yadak, IR
1 Business Studies and Development Office, Saipa Yadak, IR
Source
National Journal of System and Information Technology, Vol 10, No 1 (2017), Pagination: 81-90Abstract
The present study presents a comparative analysis of different measurement scale (i.e. linear, power, and so on) and normalization method (i.e. vector, linear, and so on.) in TOPSIS, by testing them against conventional TOPSIS assumption (in the absence of any other standards, the priorities provided by the conventional TOPSIS was used as the benchmark). In this study, the following two questions are considered:1. Does a decision priorities changed when using different measurement scale and normalization method? and 2. Does the same results of the conventional TOPSIS, be obtained from the modified TOPSIS (in other words: TOPSIS with different measurement scale and normalization method)? It is shown that, the different measurement scale and normalization method can be lead to different priorities (rank and preference intensities). Also, the modified TOPSIS priorities (TOPSIS with geometric measurement scale and logarithmic normalization method), the only or best combination that is roughly equivalent priorities as compared with conventional TOPSIS. So, we suggest (after the more experimental research in future) the modified TOPSIS method as the alternative solution.Keywords
TOPSIS, Modified TOPSIS, Measurement Scale, Normalization Method.References
- Deng H. et al., 2000,"inter company comparison using modified topsis with objective weights", computer & operations research, 27, 963-973.
- Hwang C. L. and K. Yoon, 1981,"multiple attribute decision making; methods and applications", Springer Verlag, 1981.
- Irvani Z. et al. , 2009, "an algorithm for the calculation of progress or regress via topsis and malmquist productivity index", Applied Mathematical Science, vol. 3, no. 52, 2553-2562.
- Ishizaka A. et al., 2011, "Influence of Aggregation and Measurement Scale on Ranking a compromise Alternative in AHP", journal of the operational research society, 62(4), 700-710.
- Lin Y. H. et al., 2008, "multi attribute group decision making model under the condition of uncertain information", Automation in construction, 17 (2008) 792-797.
- Luce R.D., 1997,"Quantification and Symmetry", British journal of Psychology, 88,395-398.
- Olson D. L., 2004, "comparison of weights in topsis models", Mathematical and Computer Modeling, Pergamon, 1 : 1-7.
- Pavl D.M., 2000, "Normalization of attribute values in MADM violates the conditions of consistent choice IV, DI and α ", Yugoslav journal of operations research, 1,109-122.
- Ramanathan R., 2001, "A note to the use of the AHP for environmental impact assessment”, journal of Environmental Management, 63, 27-35.
- Ren L. et al.,2007,"comparative analysis of a novel M-topsis method and topsis", Applied Mathematics Research Express, vol. 2007, 1-10.
- Roghanian et al. (2010),comparison of first aggregation and last aggregation in fuzzy group TOPSIS. Applied mathematical modeling, 34 (2010), 3754-3766.
- Stevens S. S. , 1946,"On the theory of scales of measurement", SCIENCE, 103, No.2684, 677-680.
- Tayeb S. et al., 2007, "equipment selection by numerical resolution of the Hessian matrix and topsis algorithm", Asian Journal of Information Technology, 6(1), 81-88.
- Yue Z., 2013, "An avoiding information approach to group decision making", Applied mathematical Modeling, Vol. 37 (2013), 112-126.
- Zavadeskas E. K. et al.,2006,"evaluation of ranking accuracy in multi criteria decisions", Informatica, vol. 17, no. 4, 601-618.
- Zavadskas E.K. and Z. Turskis, 2008"A new Logarithmic Normalization method in Game theory", Informatica 19, No.2, 303-314.
- Zavadskas E.K. et al., 2010,"Attributes weights determining peculiarities in Multiple Attribute Decision Making methods", Engineering Economics, 21(1), 32-43.
- A Comparative Analysis of Different Measurement Scale and Normalization Method Performances in ELECTRE Method
Abstract Views :270 |
PDF Views:6
Authors
Affiliations
1 Business Studies and Development Office, Saipa Yadak, IR
1 Business Studies and Development Office, Saipa Yadak, IR
Source
National Journal of System and Information Technology, Vol 10, No 2 (2017), Pagination: 127-138Abstract
There are several preference measurement scale and normalization method in the literature. In this paper, we compare these possibilities in ELECTRE method, and compares results. In the absence of any other standards, the priorities provided by the original ELECTRE (involve: Linear scale, Vector normalization and Entropy weights) was used as the benchmark. The results indicate that linear measurement scale and vector normalization method is not the only or best scale and normalization method in ELECTRE method. In other words, the ranking for some measurement scale (i.e. Linear, Power, Logarithmic and Root Square measurement scales) and normalization method (i.e. non-linear normalization method) are effectively same, as the benchmark.Keywords
ELECTRE, Measurement Scale, Normalization Method.References
- Alinezhad A. and A. Amini,(2011)," sensitivity analysis of Topsis technique: the results of change in the weight of one attribute on the final ranking of alternatives", Journal of optimization in industrial engineering, 7(2011), pp. 23-28.
- Amiri m. et al., (2008)," developing a new ELECTRE method with interval data in multiple attributes decision making problems", journal of applied sciences, 8(22): pp., 4017-4028.
- Azadfallah, M. (2015). A Multiple Attribute Group Decision Making model for selecting the best supplier. International Journal of Business Analytics and Intelligence, 3(2), 13-19.
- Hwang C. L. and K. Yoon, (1981)," multiple attribute decision making; methods and applications", Springer - Verlag.
- Ishizaka A. et al., (2011), "Influence of Aggregation and Measurement Scale on Ranking a compromise Alternative in AHP", journal of the operational research society, 62(4), 700-710.
- Luce R.D., (1997),"Quantification and Symmetry", British journal of Psychology, 88,395-398.
- Pavl D.M., (2000), "Normalization of attribute values in MADM violates the conditions of consistent choice IV, DI and α", Yugoslav journal of operations research, 1,109-122.
- Ramanathan R.,(2001),"A note to the use of the AHP for environmental impact assessment”, journal of Environmental Management, 63, 27-35.
- Shofade O. J. S., (2011),"considering hierarchical structure of criteria in ELECTRE decision aiding methods, master thesis, Poznan University of technology, Poland.
- Stevens S. S. , (1946) ,"On the theory of scales of measurement", SCIENCE, 103, No.2684, 677-68
- Zavadskas E.K. et al., (2010),"Attributes weights determining peculiarities in Multiple Attribute Decision Making methods", Engineering Economics, 21(1), 32-43.
- Zavadskas E.K. and Z. Turskis, (2008)"A new Logarithmic Normalization method in Game theory", Informatica 19, No.2, 303-314.
- Zopounidis C. and P. M. Pardalos, (2010)," Handbook of multi criteria analysis, applied optimization (chapter 3, by: Figueira J. K. et al.), Springer - Verlag Berlin Heidelberg.
- Two New Eigenvector-based Approaches to Assign Weights to Decision Makers in Group Decision Making under Multiple Criteria
Abstract Views :135 |
PDF Views:0
Authors
Affiliations
1 Research and Science Branch, Islamic Azad University, Tehran, IR
1 Research and Science Branch, Islamic Azad University, Tehran, IR