scholarly journals LOGISTICS FREIGHT CENTER LOCATIONS DECISION BY USING FUZZY-PROMETHEE

Transport ◽  
2014 ◽  
Vol 29 (4) ◽  
pp. 412-418 ◽  
Author(s):  
Birol Elevli
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Preference Ranking ◽  
Multi Criteria Decision Making ◽  
Uncertain Information ◽  
Logistics Center ◽  
Promethee Method ◽  
Fuzzy Promethee ◽  
Fuzzy Preference

Fuzzy Preference Ranking Organization METHod for Enrichment Evaluation (F-PROMETHEE) was applied for choosing among potential logistics center locations. The method combines the concept of fuzzy sets to represent uncertain information with the PROMETHEE, a subgroup of Multi-Criteria Decision-Making (MCDM) methods. Criteria are identified based on review of scientific and trade literature and inputs received from experts. The suitability of areas have been evaluated on the basis of these criteria. There are substantial uncertainties and subjectivity about site information. Therefore F-PROMETHEE method is preferred. The case study shows that this application provides reasonable results.

Novel Multi-criteria Decision-making Approaches Based on Hesitant Fuzzy Sets and Prospect Theory

2016 ◽  
Vol 15 (03) ◽  
pp. 621-643 ◽  
Author(s):  
Juan-Juan Peng ◽  
Jian-Qiang Wang ◽  
Xiao-Hui Wu
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Prospect Theory ◽  
Hausdorff Distance ◽  
Comparison Method ◽  
Distance Measures ◽  
Preference Ranking ◽  
Multi Criteria Decision Making ◽  
The Novel ◽  
Hesitant Fuzzy Sets

Hesitant fuzzy sets (HFSs), an extension of fuzzy sets, are considered to be useful in solving decision making problems where decision makers are unable to choose between several values when expressing their preferences. The purpose of this paper is to develop two hesitant fuzzy multi-criteria decision making (MCDM) methods based on prospect theory (PT). First, the novel component-wise ordering method for two hesitant fuzzy numbers (HFNs) is defined; however, this method does not consider the length of the two HFNs. Second, by utilizing the directed Hausdorff distance between two imprecise point sets, the generalized hesitant Hausdorff distance is developed, which overcomes the shortcomings of the existing distance measures. Third, based on the proposed comparison method and distance, as well as PT, the extended TODIM and Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE) approaches are developed in order to solve MCDM problems with hesitant fuzzy information. Finally, a practical example is provided to illustrate the pragmatism and effectiveness of the proposed approaches. Sensitivity and comparison analyses are also conducted using the same example. The findings indicate that the proposed methods do not require complicated computation procedures, yet still yield a reasonable and credible solution.

scholarly journals Study on bond selection under intuitionistic fuzzy conditions

2018 ◽  
Vol 12 (4) ◽  
pp. 376-386 ◽  
Author(s):  
Xiao-Guang Zhou ◽  
Yang-Fan Ding ◽  
Mi Lu
Keyword(s):  
Decision Making ◽  
Analytic Network Process ◽  
Uncertain Information ◽  
Preference Relations ◽  
Intuitionistic Fuzzy ◽  
Comprehensive Method ◽  
Fuzzy Preference Relations ◽  
Network Process ◽  
Fuzzy Preference

Intuitionistic fuzzy preference relations can take membership degrees, non-membership degrees, and hesitancy degrees into account during decision making. It has good practicability and flexibility in dealing with fuzzy and uncertain information. As for analytic network process, it is performed by thinking over the interaction and feedback relationships between criteria and indices, so that an effective method is provided for multi-criteria decision making. An index system with network structure for evaluating the bonds is presented, and a comprehensive method by combining the advantages of intuitionistic fuzzy preference relations and analytic network process is proposed to select and rank the bonds. A case study is given by the proposed method as well.

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.

Some Score Functions on Fermatean Fuzzy Sets and Its Application to Bride Selection Based on TOPSIS Method

2021 ◽  
Vol 10 (3) ◽  
pp. 18-29
Author(s):  
Laxminarayan Sahoo
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Score Function ◽  
Fuzzy Topsis ◽  
Multi Criteria Decision Making ◽  
Uncertain Information ◽  
Topsis Method ◽  
Score Functions ◽  
Relative Closeness ◽  
Separation Measure

The aim of this paper is to propose some score functions for the fruitful ranking of fermatean fuzzy sets (FFSs) and fermatean fuzzy TOPSIS method based on proposed score functions. fermatean fuzzy sets proposed by Senapati and Yager can handle uncertain information more easily in the process of multi-criteria decision making (MCDM). In this paper, the authors have proposed three newly improved score functions for effective ranking of fermatean fuzzy sets. Here, they have applied the proposed score function to calculate the separation measure of each alternative from the positive and negative ideal solutions to determine the relative closeness coefficient. Based on different types of score functions, they have employed the TOPSIS method to solve the multi-criteria decision-making (MCDM) problem in which all preference information provided by the decision makers is expressed in terms of fermatean fuzzy decision matrices. Finally, a numerical example for selecting the bride form matrimonial site has been considered to illustrate the proposed method.

scholarly journals Business intelligence evaluation model in enterprise systems using fuzzy PROMETHEE

2016 ◽  
Vol 6 (3) ◽  
Author(s):  
Mansoureh Maadi ◽  
Mohammad Javidnia ◽  
Malihe Khatami
Keyword(s):  
Decision Making ◽  
Business Intelligence ◽  
Fuzzy Theory ◽  
Evaluation Model ◽  
Enterprise Systems ◽  
Practical Method ◽  
Multi Criteria Decision Making ◽  
Proposed Model ◽  
Fuzzy Promethee

In this paper, a new model to evaluate business intelligence (BI) for enterprisesystems is presented. Evaluation of BI before making decisions about buying and deploymentcan be an important decision support system for managers in organizations. In this paper, asimple and practical method is presented that evaluates BI for enterprise systems. In this way,after reviewing different papers in the literature, 34 criteria for BI specifications aredetermined, and then by applying fuzzy PROMETHEE, different enterprise systems areranked. To continue to assess the proposed model and as a case study, five enterprise systemswere selected and ranked using the proposed model. The advantages of PROMETHEE overother multi-criteria decision making methods and the use of fuzzy theory to deal withuncertainty in decision making is assessed and it is found that the proposed model can be auseful and applied method to help managers make decisions in organizations.

Multi-Criteria Decision Making for Vulnerability Mapping of Flood Hazard: A Case Study of Pune City

2019 ◽  
Vol 2 (1) ◽  
pp. 41-52
Author(s):  
Nitin Mundhe
Keyword(s):  
Decision Making ◽  
Flood Hazard ◽  
Geographical Information ◽  
Multi Criteria Decision Making ◽  
Flood Hazards ◽  
Very High Frequency ◽  
Flood Vulnerability ◽  
Natural Risk ◽  
The Town

Floods are natural risk with a very high frequency, which causes to environmental, social, economic and human losses. The floods in the town happen mainly due to human made activities about the blockage of natural drainage, haphazard construction of roads, building, and high rainfall intensity. Detailed maps showing flood vulnerability areas are helpful in management of flood hazards. Therefore, present research focused on identifying flood vulnerability zones in the Pune City using multi-criteria decision-making approach in Geographical Information System (GIS) and inputs from remotely sensed imageries. Other input data considered for preparing base maps are census details, City maps, and fieldworks. The Pune City classified in to four flood vulnerability classes essential for flood risk management. About 5 per cent area shows high vulnerability for floods in localities namely Wakdewadi, some part of the Shivajinagar, Sangamwadi, Aundh, and Baner with high risk.

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