Constrained consistency enforcement in AHP

Abstract Decision-making in the presence of intangible elements must be based on a robust, but subtle, balance between expert know-how and judgment consistency when eliciting that know-how. This balance is frequently achieved as a trade-off reached after a feedback process softens the tension frequently found between one force steadily pulling towards (full) consistency, and another force driven by expert feeling and opinion. The linearization method, developed by the authors in the framework of the analytic hierarchy process, is a pull-towards-consistency mechanism that shows the path from an inconsistent body of judgment elicited from an expert towards consistency, by suggesting optimal changes to the expert opinions. However, experts may be reluctant to alter some of their issued opinions, and may wish to impose constraints on the adjustments suggested by the consistency-enforcement mechanism. In this paper, using the classical Riesz representation theorem, the linearization method is accommodated to consider various types of constraints imposed by experts during the abovementioned feedback process.

[1]  János Fülöp,et al.  Efficient weight vectors from pairwise comparison matrices , 2016, Eur. J. Oper. Res..

[2]  Joaquín Izquierdo,et al.  Improving consistency in AHP decision-making processes , 2012, Appl. Math. Comput..

[3]  Adrianna Kozierkiewicz-Hetmańska The analysis of expert opinions' consensus quality , 2017, Inf. Fusion.

[4]  Alessio Ishizaka,et al.  Are multi-criteria decision-making tools useful? An experimental comparative study of three methods , 2018, Eur. J. Oper. Res..

[5]  Joaquín Izquierdo,et al.  Some consistency issues in multi-criteria decision making , 2017 .

[6]  Thomas L. Saaty,et al.  Decision-making with the AHP: Why is the principal eigenvector necessary , 2003, Eur. J. Oper. Res..

[7]  P. Arunagiri,et al.  Ranking of MUDA using AHP and Fuzzy AHP algorithm , 2018 .

[8]  Rosaria de F. S. M. Russo,et al.  Criteria in AHP: A Systematic Review of Literature , 2015, ITQM.

[9]  Chang Xu,et al.  A decision-making tool for determination of storage capacity in grid-connected PV systems , 2018, Renewable Energy.

[10]  Christophe Champod,et al.  Resolving differing expert opinions. , 2019, Science & justice : journal of the Forensic Science Society.

[11]  Henry Muccini,et al.  Group decision-making in software architecture: A study on industrial practices , 2018, Inf. Softw. Technol..

[12]  Xiaohan Yu,et al.  ELECTRE methods in prioritized MCDM environment , 2018, Inf. Sci..

[13]  Zhang-peng Tian,et al.  A two-fold feedback mechanism to support consensus-reaching in social network group decision-making , 2018, Knowl. Based Syst..

[14]  Enrique Herrera-Viedma,et al.  On dynamic consensus processes in group decision making problems , 2018, Inf. Sci..

[15]  Kai Wang,et al.  Uncertain dynamical system-based decision making with application to production-inventory problems , 2018 .

[16]  Silvia Carpitella,et al.  Characterization of the consistent completion of analytic hierarchy process comparison matrices using graph theory , 2018, Journal of Multi-Criteria Decision Analysis.

[17]  Silvia Carpitella,et al.  A hybrid multi-criteria approach to GPR image mining applied to water supply system maintenance , 2018, Journal of Applied Geophysics.

[18]  T. L. Saaty A Scaling Method for Priorities in Hierarchical Structures , 1977 .

[19]  Zeynep D. U. Durmusoglu,et al.  Assessment of techno-entrepreneurship projects by using Analytical Hierarchy Process (AHP) , 2018 .

[20]  Silvia Carpitella,et al.  Consistent clustering of entries in large pairwise comparison matrices , 2018, J. Comput. Appl. Math..

[21]  Keyhan Khamforoosh,et al.  Influence maximization in social networks based on TOPSIS , 2018, Expert Syst. Appl..

[22]  Jiří Franek,et al.  Judgment Scales and Consistency Measure in AHP , 2014 .

[23]  Jacek Szybowski,et al.  The improvement of data in pairwise comparison matrices , 2018, KES.

[24]  C. Bertolin,et al.  Sustainable interventions in historic buildings: A developing decision making tool , 2018, Journal of Cultural Heritage.

[25]  Joaquín Izquierdo,et al.  Balancing consistency and expert judgment in AHP , 2011, Math. Comput. Model..

[26]  Itiel E. Dror,et al.  When Expert Decision Making Goes Wrong: Consensus, Bias, the Role of Experts, and Accuracy , 2018 .

[27]  Joaquín Izquierdo,et al.  Achieving matrix consistency in AHP through linearization , 2011 .

[28]  Suree Funilkul,et al.  Rankings of the security factors of human resources information system (HRIS) influencing the open climate of work , 2017 .

[29]  Mariagrazia Dotoli,et al.  A decision-making tool for energy efficiency optimization of street lighting , 2017, Comput. Oper. Res..

[30]  Ronald R. Yager,et al.  Bidirectional possibilistic dominance in uncertain decision making , 2017, Knowl. Based Syst..

[31]  Joaquín Izquierdo,et al.  A simple formula to find the closest consistent matrix to a reciprocal matrix , 2014 .

[32]  Zenonas Turskis,et al.  Decision Making in Construction Management: AHP and Expert Choice Approach , 2017 .

[33]  Silvia Carpitella,et al.  Managing Human Factors to Reduce Organisational Risk in Industry , 2018, Mathematical and Computational Applications.

[34]  Morteza Rasti Barzoki,et al.  A group multi-criteria decision-making based on best-worst method , 2018, Comput. Ind. Eng..

[35]  Gokhan Sahin,et al.  Multi-criteria decision-making in the location selection for a solar PV power plant using AHP , 2018, Measurement.