A new multi-period optimization model for resilient-sustainable project portfolio evaluation under interval-valued Pythagorean fuzzy sets with a case study

2021 ◽  
Author(s):  
Vahid Mohagheghi ◽  
Seyed Meysam Mousavi
Keyword(s):  
Fuzzy Sets ◽  
Optimization Model ◽  
Project Portfolio ◽  
Pythagorean Fuzzy Sets ◽  
Portfolio Evaluation ◽  
Interval Valued

scholarly journals A new divergence measure of interval-valued pythagorean fuzzy sets and its application

2021 ◽  
Vol 5 (2) ◽  
pp. 9-24
Author(s):  
Arthi N ◽  
Mohana K
Keyword(s):  
Fuzzy Sets ◽  
Distance Measure ◽  
Evidence Theory ◽  
Belief Function ◽  
Divergence Measure ◽  
Pythagorean Fuzzy Sets ◽  
Practical Applications ◽  
Basic Probability ◽  
Jensen Shannon Divergence ◽  
Interval Valued

As the extension of the Fuzzy sets (FSs) theory, the Interval-valued Pythagorean Fuzzy Sets (IVPFS) was introduced which play an important role in handling the uncertainty. The Pythagorean fuzzy sets (PFSs) proposed by Yager in 2013 can deal with more uncertain situations than intuitionistic fuzzy sets because of its larger range of describing the membership grades. How to measure the distance of Interval-valued Pythagorean fuzzy sets is still an open issue. Jensen–Shannon divergence is a useful distance measure in the probability distribution space. In order to efficiently deal with uncertainty in practical applications, this paper proposes a new divergence measure of Interval-valued Pythagorean fuzzy sets,which is based on the belief function in Dempster–Shafer evidence theory, and is called IVPFSDM distance. It describes the Interval-Valued Pythagorean fuzzy sets in the form of basic probability assignments (BPAs) and calculates the divergence of BPAs to get the divergence of IVPFSs, which is the step in establishing a link between the IVPFSs and BPAs. Since the proposed method combines the characters of belief function and divergence, it has a more powerful resolution than other existing methods.

A chance-constraint programming model with interval-valued pythagorean fuzzy constraints

2021 ◽  
pp. 1-17
Author(s):  
Muhammad Touqeer ◽  
Rimsha Umer ◽  
Muhammad Irfan Ali
Keyword(s):  
Fuzzy Sets ◽  
Constraint Programming ◽  
Fuzzy Numbers ◽  
Chance Constraint ◽  
Pythagorean Fuzzy Sets ◽  
Fuzzy Constraints ◽  
Network Problems ◽  
Chance Constraint Programming ◽  
Pythagorean Fuzzy Numbers ◽  
Interval Valued

Pythagorean fuzzy sets and interval-valued Pythagorean fuzzy sets are more proficient in handling uncertain and imprecise information than intuitionistic fuzzy sets and fuzzy sets. In this article, we put forward a chance-constraint programming method to solve linear programming network problems with interval-valued Pythagorean fuzzy constraints. This practice is developed using score function and upper and lower membership functions of interval-valued Pythagorean fuzzy numbers. The feasibility of the anticipated approach is illustrated by solving an airway network application and shown to be used to solve different types of network problems with objective function having interval-valued Pythagorean fuzzy numbers by employing it on shortest path problem and minimum spanning tree problem. Furthermore, a comparative examination was performed to validate the effectiveness and usefulness of the projected methodology.

scholarly journals Introducing a multi-criteria evaluation method using Pythagorean fuzzy sets

Kybernetes ◽  
2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Vahid Mohagheghi ◽  
Seyed Meysam Mousavi ◽  
Mohammad Mojtahedi ◽  
Sidney Newton
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Large Scale ◽  
Project Selection ◽  
Scale Construction ◽  
Multi Criteria Decision Making ◽  
Content Type ◽  
Pythagorean Fuzzy Sets ◽  
Multi Criteria Evaluation

Purpose Project selection is a critical decision for any organization seeking to commission a large-scale construction project. Project selection is a complex multi-criteria decision-making problem with significant uncertainty and high risks. Fuzzy set theory has been used to address various aspects of project uncertainty, but with key practical limitations. This study aims to develop and apply a novel Pythagorean fuzzy sets (PFSs) approach that overcomes these key limitations. Design/methodology/approach The study is particular to complex project selection in the context of increasing interest in resilience as a key project selection criterion. Project resilience is proposed and considered in the specific situation of a large-scale construction project selection case study. The case study develops and applies a PFS approach to manage project uncertainty. The case study is presented to demonstrate how PFS is applied to a practical problem of realistic complexity. Working through the case study highlights some of the key benefits of the PFS approach for practicing project managers and decision-makers in general. Findings The PFSs approach proposed in this study is shown to be scalable, efficient, generalizable and practical. The results confirm that the inclusion of last aggregation and last defuzzification avoids the potentially critical information loss and relative lack of transparency. Most especially, the developed PFS is able to accommodate and manage domain expert expressions of uncertainty that are realistic and practical. Originality/value The main novelty of this study is to address project resilience in the form of multi-criteria evaluation and decision-making under PFS uncertainty. The approach is defined mathematically and presented as a six-step approach to decision-making. The PFS approach is given to allow multiple domain experts to focus more clearly on accurate expressions of their agreement and disagreement. PFS is shown to be an important new direction in practical multi-criteria decision-making methods for the project management practitioner.

scholarly journals Algorithm for solving the decision-making problems based on correlation coefficients under cubic intuitionistic fuzzy information: a case study in watershed hydrological system

2021 ◽  
Author(s):  
Harish Garg ◽  
Gagandeep Kaur
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Correlation Coefficients ◽  
Mathematical Concept ◽  
Intuitionistic Fuzzy Sets ◽  
Fundamental Properties ◽  
Intuitionistic Fuzzy ◽  
Hydrological System ◽  
Interval Valued

AbstractCubic intuitionistic fuzzy sets (CIFSs) are a powerful and relevant medium for expressing imprecise information to solve the decision-making problems. The conspicuous feature of their mathematical concept is that it considers simultaneously the hallmarks of both the intuitionistic fuzzy sets (IFSs) and interval-valued IFSs. The present paper is divided into two parts: (i) defining the correlation measures for the CIFSs; (ii) introducing the decision-making algorithm for the CIFS information. Furthermore, few of the fundamental properties of these measures are examined in detail. Based on this, we define a novel algorithm to solve the multi-criteria decision-making process and illustrate numerical examples related to watershed’s hydrological geographical areas, global recruitment problem and so on. A contrastive analysis with several existing studies is also administered to test the effectiveness and verify the proposed method.

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