Hospital Type Location Allocation Decisions by Using Pythagorean Fuzzy Sets Composition: A Case Study of COVID-19

Author(s):  
Ibrahim Yilmaz ◽  
Yagmur Arioz ◽  
Cihat Ozturk ◽  
Abdullah Yildizbasi
Kybernetes ◽  
2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Vahid Mohagheghi ◽  
Seyed Meysam Mousavi ◽  
Mohammad Mojtahedi ◽  
Sidney Newton

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.


2021 ◽  
Vol 10 (4) ◽  
pp. 230
Author(s):  
Onel Pérez-Fernández ◽  
Juan Carlos García-Palomares

Moped-style scooters are one of the most popular systems of micro-mobility. They are undoubtedly good for the city, as they promote forms of environmentally-friendly mobility, in which flexibility helps prevent traffic build-up in the urban centers where they operate. However, their increasing numbers are also generating conflicts as a result of the bad behavior of users, their unwarranted use in public spaces, and above all their parking. This paper proposes a methodology for finding parking spaces for shared motorcycle services using Geographic information system (GIS) location-allocation models and Global Positioning System (GPS) data. We used the center of Madrid and data from the company Muving (one of the city’s main operators) for our case study. As well as finding the location of parking spaces for motorbikes, our analysis examines how the varying distribution of demand over the course of the day affects the demand allocated to parking spaces. The results demonstrate how reserving a relatively small number of parking spaces for scooters makes it possible to capture over 70% of journeys in the catchment area. The daily variations in the distribution of demand slightly reduce the efficiency of the network of parking spaces in the morning and increase it at night, when demand is strongly focused on the most central areas.


2018 ◽  
Vol 52 (3) ◽  
pp. 779-805 ◽  
Author(s):  
Vedat Bayram ◽  
Hande Yaman

Shelter location and traffic allocation decisions are critical for an efficient evacuation plan. In this study, we propose a scenario-based two-stage stochastic evacuation planning model that optimally locates shelter sites and that assigns evacuees to nearest shelters and to shortest paths within a tolerance degree to minimize the expected total evacuation time. Our model considers the uncertainty in the evacuation demand and the disruption in the road network and shelter sites. We present a case study for a potential earthquake in Istanbul. We compare the performance of the stochastic programming solutions to solutions based on single scenarios and mean values.


Author(s):  
Jwngsar Moshahary

Intuitionistic or pythagorean fuzzy sets are the best tools to deal with uncertainty or ambiguity to solve diverse disciplines of application problems. It is often difficult to compute union, intersection, and complements when it comes to a large number of members contained in the set, also it is difficult to check whether it is a subset or not. Here, we used the C-programming language to overcome the problems, and then it is found that more effective and realistic results have been obtained.


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