Extension of weighted aggregated sum product assessment with interval-valued intuitionistic fuzzy numbers (WASPAS-IVIF)

The weighted aggregated sum product assessment is used to improve the accuracy of weighted sum and weighted product models.An extended version of weighted aggregated sum product assessment (WASPAS method) is proposed for soft computing.In the proposed WASPAS-IVIF method, the uncertainty is expressed by interval valued intuitionistic fuzzy numbers.Numerical example demonstrates strengths of combining IVIFS in handling uncertainty with the enhanced accuracy of WASPAS. Different methods are proposed in the framework of multi attribute utility theory for multi criteria decision making. Among the proposed methods, weighted sum and weighted product models (WSM and WPM) are well known and widely accepted. To improve the accuracy of WSM and WPM, the weighted aggregated sum product assessment (WASPAS) method was proposed which used an aggregation operator on WSM and WPM. In this paper, an extended version of WASPAS method is proposed which can be applied in uncertain decision making environment. In the proposed WASPAS-IVIF method, the uncertainty of decision maker(s) in stating their judgments and evaluations regard to criteria importance and/or alternatives performance on criteria are expressed by interval valued intuitionistic fuzzy numbers. Two numerical examples of ranking derelict buildings' redevelopment decisions and investment alternatives are presented. The results are then compared with the rankings provided by other methods such as TOPSIS-IVIF, COPRAS-IVIF and IFOWA. Combining the strengths of IVIFS in handling uncertainty with the enhanced accuracy of WASPAS makes the proposed method as a desirable method for multi criteria decision making in real world applications.

[1]  Jin-Han Park,et al.  Extension of the VIKOR method for group decision making with interval-valued intuitionistic fuzzy information , 2011, Fuzzy Optim. Decis. Mak..

[2]  E. Zavadskas,et al.  A complex proportional assessment method for group decision making in an interval-valued intuitionistic fuzzy environment , 2013 .

[3]  Evangelos Triantaphyllou,et al.  An examination of the effectiveness of multi-dimensional decision-making methods: A decision-making paradox , 1989, Decis. Support Syst..

[4]  Nils Brunsson My own book review : The Irrational Organization , 2014 .

[5]  Zhou-Jing Wang,et al.  An approach to multiattribute decision making with interval-valued intuitionistic fuzzy assessments and incomplete weights , 2009, Inf. Sci..

[6]  Shyi-Ming Chen,et al.  Multiattribute decision making based on interval-valued intuitionistic fuzzy values , 2012, Expert Syst. Appl..

[7]  Edmundas Kazimieras Zavadskas,et al.  Decision making on business issues with foresight perspective; an application of new hybrid MCDM model in shopping mall locating , 2013, Expert Syst. Appl..

[8]  Yi Lin,et al.  Grey Systems: Theory and Applications , 2010 .

[9]  E. Zavadskas,et al.  Multiple criteria decision making (MCDM) methods in economics: an overview , 2011 .

[10]  E. Zavadskas,et al.  Optimization of Weighted Aggregated Sum Product Assessment , 2012 .

[11]  Dejian Yu,et al.  Interval-valued intuitionistic fuzzy prioritized operators and their application in group decision making , 2012, Knowl. Based Syst..

[12]  Ivor Grattan-Guinness,et al.  Fuzzy Membership Mapped onto Intervals and Many-Valued Quantities , 1976, Math. Log. Q..

[13]  Jurgita Antucheviciene,et al.  Measuring Congruence of Ranking Results Applying Particular MCDM Methods , 2011, Informatica.

[14]  Deng-Feng Li,et al.  Linear programming method for MADM with interval-valued intuitionistic fuzzy sets , 2010, Expert Syst. Appl..

[15]  J. H. Park,et al.  Extension of the TOPSIS method for decision making problems under interval-valued intuitionistic fuzzy environment , 2011 .

[16]  Pedro Burillo López,et al.  A theorem for constructing interval-valued intuitionistic fuzzy sets from intuitionistic fuzzy sets , 1995 .

[17]  Zeshui Xu,et al.  Generalized aggregation operators for intuitionistic fuzzy sets , 2010 .

[18]  Fei Ye,et al.  An extended TOPSIS method with interval-valued intuitionistic fuzzy numbers for virtual enterprise partner selection , 2010, Expert Syst. Appl..

[19]  M. K. Starr,et al.  Executive decisions and operations research , 1970 .

[20]  Richard Bellman,et al.  Decision-making in fuzzy environment , 2012 .

[21]  Reza Tavakkoli-Moghaddam,et al.  Soft computing based on new interval-valued fuzzy modified multi-criteria decision-making method , 2013, Appl. Soft Comput..

[22]  Z. Xu,et al.  Methods for aggregating interval-valued intuitionistic fuzzy information and their application to decision making , 2007 .

[23]  Weize Wang,et al.  The multi-attribute decision making method based on interval-valued intuitionistic fuzzy Einstein hybrid weighted geometric operator , 2013, Comput. Math. Appl..

[24]  Diyar Akay,et al.  A multi-criteria intuitionistic fuzzy group decision making for supplier selection with TOPSIS method , 2009, Expert Syst. Appl..

[25]  Po-Lung Yu,et al.  Forming Winning Strategies: An Integrated Theory of Habitual Domains , 1990 .

[26]  Deng-Feng Li,et al.  Extension principles for interval-valued intuitionistic fuzzy sets and algebraic operations , 2011, Fuzzy Optim. Decis. Mak..

[27]  Jurgita Antucheviciene,et al.  Multiple criteria evaluation of rural building's regeneration alternatives , 2007 .

[28]  Didier Dubois,et al.  The role of fuzzy sets in decision sciences: Old techniques and new directions , 2011, Fuzzy Sets Syst..

[29]  Rakesh Verma,et al.  Facility Location Selection: An Interval Valued Intuitionistic Fuzzy TOPSIS Approach , 2010 .

[30]  Jurgita Antuchevičienė,et al.  ASSESSMENT OF HEALTH AND SAFETY SOLUTIONS AT A CONSTRUCTION SITE , 2013 .

[31]  Krassimir T. Atanassov,et al.  Intuitionistic fuzzy sets , 1986 .

[32]  Edmundas Kazimieras Zavadskas,et al.  To modernize or not: Ecological–economical assessment of multi-dwelling houses modernization , 2013 .