Open AccessAn Assessment of Objectivity Convergence of Fuzzy TOPSIS Method Extended With Rank Order Weights in Group Decision Making
Author(s) -
Ayan Chattopadhyay,
Upasana Bose
Publication year - 2018
Publication title -
asian journal of managerial science/asian journal of managerial science
Language(s) - English
Resource type - Journals
eISSN - 2583-9810
pISSN - 2249-6300
DOI - 10.51983/ajms-2018.7.3.1347
Subject(s) - topsis , vagueness , rank (graph theory) , mathematical optimization , mathematics , fuzzy logic , pairwise comparison , centroid , objectivity (philosophy) , convergence (economics) , ideal solution , computer science , data mining , operations research , artificial intelligence , statistics , economics , combinatorics , philosophy , physics , epistemology , economic growth , thermodynamics
Group decision making in a multi criteria environment is a familiar business situation where the decision makers identify an ideal choice, among many. The situation gets complex when decision makers do not have crisp data to deal with. The fuzzy TOPSIS method, and its likes, provides solution to such problems and the criteria weight plays a determinant role in the overall priority estimation. This paper presents an extended fuzzy TOPSIS approach by incorporating criteria weights derived from rank order. It considers three criteria weights; the rank order centroid, rank sum and rank reciprocal weights. The criteria weights are calculated separately and integrated with fuzzy TOPSIS method to rank choices. Finally, objectivity convergence of the alternative rankings is tested. The proposed method yields a fairly uniform and consistent result in the case of supply chain management and anticipates wide application in multi criteria environment, concomitant with uncertainty and vagueness.