Fuzzy multiattribute decision-making models and methods with incomplete preference information

1999 ◽  
Vol 106 (2) ◽  
pp. 113-119 ◽  
Author(s):  
Dengfeng Li
Keyword(s):  
Decision Making ◽  
Preference Information ◽  
Incomplete Preference ◽  
Decision Making Models

An Interactive Signed Distance Approach for Multiple Criteria Group Decision-Making Based on Simple Additive Weighting Method with Incomplete Preference Information Defined by Interval Type-2 Fuzzy Sets

2014 ◽  
Vol 13 (05) ◽  
pp. 979-1012 ◽  
Author(s):  
Ting-Yu Chen
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Preference Information ◽  
Incomplete Preference ◽  
Signed Distance ◽  
Decision Making Problem ◽  
Simple Additive Weighting ◽  
Interval Type

Interval type-2 fuzzy sets (T2FSs) with interval membership grades are suitable for dealing with imprecision or uncertainties in many real-world problems. In the Interval type-2 fuzzy context, the aim of this paper is to develop an interactive signed distance-based simple additive weighting (SAW) method for solving multiple criteria group decision-making problems with linguistic ratings and incomplete preference information. This paper first formulates a group decision-making problem with uncertain linguistic variables and their transformation to interval type-2 trapezoidal fuzzy numbers. Concerning the relative importance of multiple decision-makers and group consensus of fuzzy opinions, a procedure using hybrid averages is then employed to construct a collective decision matrix. By an appropriate extension of the classical SAW approach, this paper utilizes the concept of signed distances and establishes an integrated programming model to manage multi-criteria group decisions under the incomplete and inconsistent preference structure. Further, an interactive procedure is established for group decision making. Finally, the feasibility and effectiveness of the proposed methods are illustrated by a collaborative decision-making problem of patient-centered care (PCC).

Information support for expert evaluation of the states of the external environment

2020 ◽  
pp. 71-76
Author(s):  
Rasol Murtadha Najah
Keyword(s):  
Decision Making ◽  
Environmental Conditions ◽  
Fuzzy Inference ◽  
Environmental Parameters ◽  
Information Support ◽  
Expert Assessment ◽  
Fuzzy Variables ◽  
Decision Making Models ◽  
The Difference ◽  
State Of The Environment

This article discusses the application of methods to enhance the knowledge of experts to build a decision-making model based on the processing of physical data on the real state of the environment. Environmental parameters determine its ecological state. To carry out research in the field of expert assessment of environmental conditions, the analysis of known works in this field is carried out. The results of the analysis made it possible to justify the relevance of the application of analytical, stochastic models and models based on methods of enhancing the knowledge of experts — experts. It is concluded that the results of using analytical and stochastic objects are inaccurate, due to the complexity and poor mathematical description of the objects. The relevance of developing information support for an expert assessment of environmental conditions is substantiated. The difference of this article is that based on the analysis of the application of expert methods for assessing the state of the environment, a fuzzy logic adoption model and information support for assessing the environmental state of the environment are proposed. The formalization of the parameters of decision-making models using linguistic and fuzzy variables is considered. The formalization of parameters of decision-making models using linguistic and fuzzy variables was considered. The model’s description of fuzzy inference is given. The use of information support for environment state assessment is shown on the example of experts assessing of the land desertification stage.

Information technology support for integrated supply chain modeling

2008 ◽  
Vol 27 (1) ◽  
pp. 3-13
Author(s):  
Charu Chandra ◽  
Jānis Grabis
Keyword(s):  
Decision Making ◽  
Information Technology ◽  
Supply Chain ◽  
Process Modeling ◽  
Service Oriented Architecture ◽  
Model Development ◽  
Integrated Models ◽  
Supply Chain Modeling ◽  
Decision Making Models ◽  
Integrated Supply Chain

Multiple interrelated decision-making models are frequently used in supply chain modeling. Model integration is a precondition for efficient development and utilization of these models. This paper discusses use of modern information technology (IT) techniques and methods for integration of supply chain decision-making models. The overall approach to using IT at various stages of model development is presented. Data and process modeling techniques are used to developed semi-formalized representation of integrated models. These models support integration of decision-making components with other parts of supply chain information system. Process modeling is also used to describe interrelationships among multiple decision-making models. This representation is used as the basis for implementation of integrated models. The service-oriented architecture is proposed as an implementation platform. The presented discussion serves as the basis for further developments in developing integrated supply chain decision-making models.

scholarly journals Approaches for multicriteria decision-making based on the hesitant fuzzy best–worst method

2021 ◽  
Author(s):  
Jian Li ◽  
Li-li Niu ◽  
Qiongxia Chen ◽  
Zhong-xing Wang
Keyword(s):  
Decision Making ◽  
Comparative Analysis ◽  
Programming Model ◽  
Multicriteria Decision Making ◽  
Decision Makers ◽  
Multicriteria Decision ◽  
Preference Relations ◽  
Fuzzy Preference Relations ◽  
Decision Making Models ◽  
Best Worst Method

AbstractHesitant fuzzy preference relations (HFPRs) have been widely applied in multicriteria decision-making (MCDM) for their ability to efficiently express hesitant information. To address the situation where HFPRs are necessary, this paper develops several decision-making models integrating HFPRs with the best worst method (BWM). First, consistency measures from the perspectives of additive/multiplicative consistent hesitant fuzzy best worst preference relations (HFBWPRs) are introduced. Second, several decision-making models are developed in view of the proposed additive/multiplicatively consistent HFBWPRs. The main characteristic of the constructed models is that they consider all the values included in the HFBWPRs and consider the same and different compromise limit constraints. Third, an absolute programming model is developed to obtain the decision-makers’ objective weights utilizing the information of optimal priority weight vectors and provides the calculation of decision-makers’ comprehensive weights. Finally, a framework of the MCDM procedure based on hesitant fuzzy BWM is introduced, and an illustrative example in conjunction with comparative analysis is provided to demonstrate the feasibility and efficiency of the proposed models.

New advances in attitude and behavioural decision-making models

2014 ◽  
Vol 30 (5-6) ◽  
pp. 519-528 ◽  
Author(s):  
Nina Michaelidou ◽  
Louise Hassan
Keyword(s):  
Decision Making ◽  
Decision Making Models
Sign in / Sign up

Export Citation Format

Share Document