A New Interval Type-2 Fuzzy Decision Method with an Extended Relative Preference Relation and Entropy to Project Critical Path Selection

2019 ◽  
Vol 8 (1) ◽  
pp. 19-47 ◽  
Author(s):  
Y. Dorfeshan ◽  
S.M. Mousavi
Keyword(s):  
Critical Path ◽  
Preference Relation ◽  
Entropy Method ◽  
Path Selection ◽  
Decision Method ◽  
Relative Preference ◽  
Relative Closeness ◽  
Critical Path Selection ◽  
Interval Type

Considering uncertainty in multi-criteria decision making (MCDM) is an important issue in today's business and management problems. In this article, to use advantages of IT2FSs, a novel interval type-2 fuzzy multi-criteria decision method is presented with an extended entropy and relative preference relation. To tackle vagueness and uncertainty of real-world problems, the IT2FSs are used and applied to a modified MCDM method. Furthermore, an entropy method is developed under an IT2F environment and for obtaining the final weight of each criterion, a relative preference relation is hybridized with an entropy method. Also, the weight of each decision maker (DM) is calculated by a new IT2F-order preference method by means of the relative closeness. Finally, an existing example about the project critical path selection by considering effective criteria, such as time, cost, quality and safety, is adopted from the literature and solved to indicate the capability of introduced method.

Soft Computing Based on an Interval Type-2 Fuzzy Decision Model for Project-Critical Path Selection Problem

2018 ◽  
Vol 5 (1) ◽  
pp. 1-24
Author(s):  
Y. Dorfeshan ◽  
S. Meysam Mousavi
Keyword(s):  
Fuzzy Sets ◽  
Critical Path ◽  
Preference Relation ◽  
Path Selection ◽  
Analysis Model ◽  
Relative Preference ◽  
Critical Path Selection ◽  
Fuzzy Decision Model ◽  
Interval Type

This article describes how project managers are faced with the conflicting criteria to make their decisions. In many real-world conditions, it may be difficult to get certain information about activities attributes, including time, cost, risk, and quality. In this case, interval type-2 fuzzy sets (IT2FSs) which consider more uncertainty than type-1 fuzzy sets (T1FSs) are used. In this article, a new group multi-criteria analysis model is expressed based on new compromise solution and relative preference relation (RPR) concept under IT2FSs environment. Also, a new version of the evaluation on distance from average solution (EDAS) method is introduced to specify the weight of each expert under IT2FSs. Furthermore, the RPR is more reasonable than the defuzzification approach. In fact, the RPR not only can provide preference degree between two fuzzy numbers but also can keep some information. Finally, an application from literature is adopted and solved to demonstrate the applicability of proposed method.

scholarly journals Non-enumerative Generation of Path Delay Distributions and Its Application to Critical Path Selection

2016 ◽  
Vol 22 (1) ◽  
pp. 1-21 ◽  
Author(s):  
Ahish Mysore Somashekar ◽  
Spyros Tragoudas ◽  
Rathish Jayabharathi ◽  
Sreenivas Gangadhar
Keyword(s):  
Critical Path ◽  
Path Selection ◽  
Path Delay ◽  
Critical Path Selection

scholarly journals An Approach for Achieving Consistency for Symmetric Trapezoidal Interval Type-2 Fuzzy Sets

2019 ◽  
Vol 2019 ◽  
pp. 1-16
Author(s):  
Jiuping Xu ◽  
Kang Xu
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Preference Relation ◽  
Mapping Method ◽  
Linguistic Terms ◽  
Actual Case ◽  
Preference Relations ◽  
Interval Type

Interval type-2 fuzzy sets (IT2 FSs) are powerful tools for dealing with linguistic information in decision making. However, there is a dearth of research regarding the consistency of preference relations based on IT2 FSs. In this paper, symmetric IT2 FSs and IT2 additive preference relations are defined, whilst at the same time a mapping method is proposed to convert IT2 numbers into the corresponding linguistic terms based on the ranking values for IT2 FSs, and some properties for symmetric IT2 FSs are proved. Then, we discuss the process for achieving consistency for IT2 additive preference relations. An algorithm is developed for the IT2 additive preference relation process for achieving consistency, and some desired algorithmic properties are proved. Finally, an actual case study is used in order to demonstrate the effectiveness of the proposed approach.

Sign in / Sign up

Export Citation Format

Share Document