A new approach for solving balanced and/or unbalanced intuitionistic fuzzy assignment problems

2016 ◽  
Vol 9 (12) ◽  
pp. 2382
Author(s):  
M. Jayalakshmi
2020 ◽  
Vol 9 (1) ◽  
pp. 1-34 ◽  
Author(s):  
P. Senthil Kumar

When people solve real-life SAP they tend to face the uncertainty state as well as hesitation due to many uncontrollable factors. To deal with uncertainty and hesitation many authors have suggested the intuitionistic fuzzy representation for the data. In this article, the author tried to categorise the SAP under uncertain environment. He formulates the IFSAP and utilizes the TIFN to deal with uncertainty and hesitation. The SAP has uncertainty and hesitation in cost/time/profit/production is known as FIFSAP. The PSK (P. Senthil Kumar) method for finding an optimal solution for FIFAP is extended to solve the FIFSAP and the optimal objective value of FIFSAP is obtained in terms of TIFN. The main advantage of this method is that the optimal solution/assignment of FIFSAP is obtained without using the Hungarian method and intuitionistic fuzzy reduction method. Moreover, the proposed method is computationally very simple and easy to understand. The numerical example is presented to demonstrate computing procedure. The results affirm efficiency of the proposed method.


This article addresses the 3-dimensional mixed intuitionistic fuzzy assignment problems (3D-MIFAPs). In this article, firstly, the author formulates an assignment problem (AP) and assumes the parameters are in uncertainty with hesitation. Secondly, based on the nature of the parameter the author defines various types of solid assignment problem (SAP) in uncertain environment. Thirdly, to solve 3D-MIFAP the PSK method for finding an optimal solution of fully intuitionistic fuzzy assignment problem (FIFAP) is extended by the author. Fourthly, the author presents the proofs of the proposed theorems and corollary. Fifthly, the proposed approach is illustrated with three numerical examples and the optimal objective value of 3D-MIFAP is obtained in the form of intuitionistic fuzzy number and the solution is checked with MATLAB and their coding are also given by the author. Sixthly, the author presents the comparison results and their graphical representation, merits and demerits of the proposed and existing methods and finally the author presents conclusion and future research directions.


2022 ◽  
Vol 11 (1) ◽  
pp. 1-10
Author(s):  
Pinaki Majumdar

In this paper a new definition of Intuitionistic fuzzy multisets (IFMS) has been introduced. Algebraic operations on these intuitionistic fuzzy multisets are defined and their properties under these algebraic operations are studied. The author has also introduced a new notion of complement for an IFMS in which the complement of the original set is also an IFMS. The notion of distance and similarity between two IFMS’s has been defined and their properties have also been studied here. An application of IFMS in solving a medical diagnosis problem has been provided at the end.


2020 ◽  
Vol 39 (3) ◽  
pp. 3519-3543
Author(s):  
Xue Deng ◽  
Chuangjie Chen

The purpose of this paper is to solve the portfolio selection problem when historical data are unavailable. In this paper, the problem is viewed as a multi-criteria decision making (MCDM) problem under intuitionistic fuzzy circumstances, and the prospect theory is utilized to reflect decision makers’ psychological state, which is always bounded rational. Therefore, a new approach to solve MCDM problems is presented based on the following improvements. (a) The entropy-weighted method with extreme data resistance is proposed instead of weight function to deal with the weight of criteria, because weight stands for the decision maker’s preference of criteria rather than objective probability and should not be distorted. (b) A new entropy-weighted method with confidence degree is presented, which can not only describe the uncertainty of information each criterion provides but also reflect the decision maker’s confidence in the information. (c) To reduce the interference from extreme data, the median is selected as reference point instead of mean or extreme value. (d) Based on the distance measure, the intuitionistic fuzzy prospect value function is presented to capture decision makers’ psychological state. Finally, a novel model with prospect value constraint and risk preference is constructed to allocate investment ratios. For our proposed method and model, two numerical applications are given to verify their validity and the sensitivity analysis is carried out to illustrate their practical significance.


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