Ranking based on optimal points multi-criteria decision-making method

The purpose of this paper is to propose a new MCDM method called ranking based on optimal points (RBOP).,By employing two abstract groups of alternatives as the optimum alternatives and an optimal alternative, in order to offer the most desirable alternative, RBOP imitates human behavior in the decision-making process. RBOP policy is to find the best alternative through measuring alternatives distances from optimum alternatives and optimal alternative, thus, the best alternative must be sitting on the closest distance to its optimum points and the closest distance to the optimal points simultaneously.,In this paper, the author introduced a ten-step gray form of RBOP which is applied in a case of buying running shoes and results compared to the existing MCDM methods. Results showed the considerable differences.,Generally, in order to select the best alternative(s), and to aid decision makers (DMs) to make better decisions for the real-world problems, MCDM methods evaluate a number of alternatives via a number of criteria through the proposed mathematical algorithms. Frequently, for the direct impact of the DMs on the decision-making process, MCDM methods have inflexible algorithms. They only allow DMs to make an impact on the criteria analysis. The inflexibility emerges as a problem when perfect information is available for DMs and MCDM final results are not desirable. The process of the new method completely depends on DMs’ decisions, their interpretation of the periphery and their personal impressions. Hence, the output of RBOP is not necessarily the best alternative, but it offers the most desirable alternative to DM.

[1]  Gwo-Hshiung Tzeng,et al.  Extended VIKOR method in comparison with outranking methods , 2007, Eur. J. Oper. Res..

[2]  K R MacCrimmon,et al.  Decisionmaking among Multiple-Attribute Alternatives: A Survey and Consolidated Approach , 1968 .

[3]  Seyed Jafar Sadjadi,et al.  Best-worst multi-criteria decision-making method: A robust approach , 2018 .

[4]  M. Modarres,et al.  Robust supply chain coordination modeling: A revenue management perspective , 2009 .

[5]  Bertrand Mareschal,et al.  Prométhée: a new family of outranking methods in multicriteria analysis , 1984 .

[6]  Shervin Zakeri,et al.  Systematic combination of fuzzy and grey numbers for supplier selection problem , 2015, Grey Syst. Theory Appl..

[7]  Yingxu Wang,et al.  The Cognitive Process of Decision Making , 2007, Int. J. Cogn. Informatics Nat. Intell..

[8]  Gwo-Hshiung Tzeng,et al.  Fuzzy Multicriteria Model for Postearthquake Land-Use Planning , 2003 .

[9]  Jean G. Padioleau Decisions and Organizations , 1989 .

[10]  Prasenjit Chatterjee,et al.  Materials selection using complex proportional assessment and evaluation of mixed data methods , 2011 .

[11]  Zhang Ren,et al.  Confidence assessment and interval prediction for multi-input model via grey system theory , 2017, Grey Syst. Theory Appl..

[12]  H. Simon Rational Decision Making in Business Organizations , 1978 .

[13]  Robert LIN,et al.  NOTE ON FUZZY SETS , 2014 .

[14]  J. Shanteau,et al.  Introduction: Where to decision making , 2003 .

[15]  Roman Senkerik,et al.  Comparison of MCDM methods with users' evaluation , 2016, 2016 11th Iberian Conference on Information Systems and Technologies (CISTI).

[16]  Xiaozhan Xu,et al.  The SIR method: A superiority and inferiority ranking method for multiple criteria decision making , 2001, Eur. J. Oper. Res..

[17]  Sifeng Liu,et al.  A new approach in animal diet using grey system theory , 2018, Grey Syst. Theory Appl..

[18]  M. Bohanec,et al.  The Analytic Hierarchy Process , 2004 .

[19]  Zenonas Turskis,et al.  Integrated Fuzzy Multiple Criteria Decision Making Model for Architect Selection , 2012 .

[20]  Bernard Roy,et al.  Classement et choix en présence de points de vue multiples , 1968 .

[21]  George P. Huber,et al.  The nature of organizational decision making and the desig n of decision support systems , 1981 .

[22]  R. H. Franke The Unbounded Mind: Breaking the Chains of Traditional Business Thinking , 1993 .

[23]  A. Tversky Elimination by aspects: A theory of choice. , 1972 .

[24]  Naiming Xie,et al.  New axiomatic approach to the concept of grey information , 2018, Grey Syst. Theory Appl..

[25]  Anish Sachdeva,et al.  Multi-factor failure mode critically analysis using TOPSIS , 2009 .

[26]  A. U.S.,et al.  Measuring the efficiency of decision making units , 2003 .

[27]  F. T. Rocha,et al.  Cognitive Brain Mapping Used in the Study of Entrepreneurial Behavior – Pilot Test with the Use of Electroencephalogram - EEG during the Process of Identification of Business Opportunities , 2016 .

[28]  Sang Joon Kim,et al.  A Mathematical Theory of Communication , 2006 .

[29]  Thomas L. Saaty,et al.  On polynomials and crossing numbers of complete graphs , 1971 .

[30]  Alan Jessop,et al.  IMP: A decision aid for multiattribute evaluation using imprecise weight estimates , 2014 .

[31]  Kalyanmoy Deb,et al.  Multiple Criteria Decision Making, Multiattribute Utility Theory: Recent Accomplishments and What Lies Ahead , 2008, Manag. Sci..

[32]  H. Simon,et al.  The New Science of Management Decision, Revised Edition. , 1977 .

[33]  T. Das,et al.  Cognitive Biases and Strategic Decision Processes: An Integrative Perspective , 1999 .

[34]  E. Reissner On asymptotic solutions for nonsymmetric deformations of shallow shells of revolution , 1964 .

[35]  Yi Peng,et al.  Evaluation of Classification Algorithms Using MCDM and Rank Correlation , 2012, Int. J. Inf. Technol. Decis. Mak..

[36]  Herbert A. Simon,et al.  The new science of management decision , 1960 .

[37]  Ching-Lai Hwang,et al.  Methods for Multiple Attribute Decision Making , 1981 .

[38]  I. Turksen,et al.  Uncertainty and Fuzzy Decisions , 2014 .

[39]  Bernard Roy,et al.  Problems and methods with multiple objective functions , 1971, Math. Program..

[40]  Yi Lin,et al.  Theory of grey systems: capturing uncertainties of grey information , 2004 .

[41]  Goutam Kumar Bose,et al.  Multi criteria FMECA for coal-fired thermal power plants using COPRAS-G , 2014 .

[42]  J. Rezaei Best-worst multi-criteria decision-making method , 2015 .

[43]  Naiming Xie,et al.  Novel methods on comparing grey numbers , 2010 .

[44]  J. P. King,et al.  Statistical and analytical comparison of multi-criteria decision-making techniques under fuzzy environment , 2016 .

[45]  Shahrul Kamaruddin,et al.  Comparison of Multi Criteria Decision Making Methods From The Maintenance Alternative Selection Perspective , 2013 .

[46]  Gautam Mitra,et al.  Mathematical Models for Decision Support , 1987, NATO ASI Series.

[47]  Deng Ju-Long,et al.  Control problems of grey systems , 1982 .

[48]  Gwo-Hshiung Tzeng,et al.  Multicriteria Planning of Post‐Earthquake Sustainable Reconstruction , 2002 .