scholarly journals Fuzzy Multicriteria Modelling of Decision Making in the Renewal of Healthcare Technologies

Mathematics ◽  
2020 ◽  
Vol 8 (6) ◽  
pp. 944 ◽  
Author(s):  
Sergio Domínguez ◽  
María Carmen Carnero
Keyword(s):  
Decision Making ◽  
Care Staff ◽  
Analytic Hierarchy ◽  
Labview Software ◽  
Fuzzy Environment ◽  
Multicriteria Model ◽  
Healthcare Technologies ◽  
Care Requirements ◽  
Hierarchy Process

In the current literature, there are a clear lack of systems to assist in making decisions about the renewal of technology for healthcare equipment, which means that the limited capacity to invest in new equipment cannot usually be appropriately applied as determined by the care requirements of a community. This may have important repercussions for patients, such as the inability to offer treatment or diagnosis, having to delay treatment or diagnosis, increase the risk of patients and care staff of using obsolete equipment, and preventing early, accurate, and reliable diagnosis, all of which have effects on the quality of care to a community. This study therefore describes the first multicriteria model in a fuzzy environment to assist in decision making related to the renewal of healthcare equipment. The fuzzy analytic hierarchy process (FAHP), which allows for ambiguities, uncertainties, and doubts inherent in real-world decision processes to be taken into account, was used to do this. The model produces a plan with actions to be taken depending on the obtained results. The model includes a novel methodology that consists of modifying the top–down technique to allow for the levels of priority for renewing healthcare equipment to be determined from judgements given by three experts. The model was validated by applying it to a set of medical devices, and we show the results for a surgical C-arm, an X-ray CT room, a neonatal ventilator, a defibrillator, and a video-colonoscope. A program was also created using the NI Labview software to process the model so that it could be applied with a user interface that acts quickly, simply, and intuitively.

Decision-Making Model for Convention Site Selection

2012 ◽  
Vol 538-541 ◽  
pp. 895-900 ◽  
Author(s):  
Han Chen Huang
Keyword(s):  
Decision Making ◽  
Site Selection ◽  
Political Conflict ◽  
Decision Makers ◽  
City Image ◽  
Analytic Hierarchy ◽  
Number Of Factors ◽  
Decision Making Model ◽  
Hierarchy Process

A number of factors must be considered when selecting a convention site. Typically, most selections are based on the decision makers’ knowledge and experience, which may lead to biased decisions based on the decision makers’ subjective judgment. This study establishes decision-making evaluation factors and attributes for convention site selection based on a literature review. After surveying experts’ opinions using questionnaires, we employed the fuzzy analytic hierarchy process (FAHP) to analyze the weighting of the factors and attributes. The results show that of the five evaluation factors, site environment is the most important, followed by meeting and accommodation facilities, local support, extraconference opportunities, and costs. Additionally, the five most important attributes among the 20 evaluation attributes are the suitability of convention facilities, suitability and quality of local infrastructure, climate, city image, and political conflict or terrorist threats.

Dynamic QoS-Aware Cloud Service Selection Using Best-Worst Method and Timeslot Weighted Satisfaction Scores

2020 ◽  
Author(s):  
Falak Nawaz ◽  
Naeem Khalid Janjua
Keyword(s):  
Decision Making ◽  
Service Selection ◽  
Cloud Service ◽  
Cloud Services ◽  
Satisfaction Score ◽  
Analytic Hierarchy ◽  
Hierarchy Process ◽  
Best Worst Method ◽  
Selection Of

Abstract The number of cloud services has dramatically increased over the past few years. Consequently, finding a service with the most suitable quality of service (QoS) criteria matching the user’s requirements is becoming a challenging task. Although various decision-making methods have been proposed to help users to find their required cloud services, some uncertainties such as dynamic QoS variations hamper the users from employing such methods. Additionally, the current approaches use either static or average QoS values for cloud service selection and do not consider dynamic QoS variations. In this paper, we overcome this drawback by developing a broker-based approach for cloud service selection. In this approach, we use recently monitored QoS values to find a timeslot weighted satisfaction score that represents how well a service satisfies the user’s QoS requirements. The timeslot weighted satisfaction score is then used in Best-Worst Method, which is a multi-criteria decision-making method, to rank the available cloud services. The proposed approach is validated using Amazon’s Elastic Compute Cloud (EC2) cloud services performance data. The results show that the proposed approach leads to the selection of more suitable cloud services and is also efficient in terms of performance compared to the existing analytic hierarchy process-based cloud service selection approaches.

scholarly journals Fusion of BWM and AHP MCDM Methods to Choose the Most Suitable Secondary School for an Individual in the Context of Bangladesh

2019 ◽  
Vol 06 (03) ◽  
pp. 311-328
Author(s):  
N. S. M. Rezaur Rahman ◽  
Md. Abdul Ahad Chowdhury ◽  
Adnan Firoze ◽  
Rashedur M. Rahman
Keyword(s):  
Decision Making ◽  
Secondary School ◽  
Pairwise Comparison ◽  
User Preferences ◽  
Multi Criteria Decision Making ◽  
Analytic Hierarchy ◽  
Final Score ◽  
Hierarchy Process ◽  
Best Worst Method

Choosing the best schools from a group of schools is a multi-criteria decision-making (MCDM) problem. In this paper, we have represented a method that uses the fusion of two multi-criteria decision-making methods, Best–Worst Method (BWM) and Analytic Hierarchy Process (AHP), to rank some of the user preferred alternatives. The system considers the choice of the user and the quality of the alternatives to rank them. User preferences on the criteria are taken as inputs in the form of best–worst comparison vectors to measure the choice of the user. These values are applied to calculate the numeric weights of each of the criteria. These weights reflect the preference of the user. A dataset of secondary schools in Bangladesh has been compiled and used for automatic quantitative pairwise comparison on the alternatives to calculate the score of each alternative in every criterion, which reflects its quality in that criterion. These scores are calculated using AHP. The weights of the criteria as well as the scores of these alternatives in those criteria are then used to calculate the final score of the alternatives and to rank them accordingly. An extensive experimental analysis and comparative study is reported at the end of this paper.

Optimal Cloud-Path Selection in Mobile Cloud Offloading Systems Based on QoS Criteria

2013 ◽  
Vol 5 (4) ◽  
pp. 30-47 ◽  
Author(s):  
Huaming Wu ◽  
Qiushi Wang ◽  
Katinka Wolter
Keyword(s):  
Historical Data ◽  
Cloud Service ◽  
Fuzzy Topsis ◽  
Path Selection ◽  
Cloud Services ◽  
Analytic Hierarchy ◽  
Fuzzy Environment ◽  
Order Preference ◽  
Hierarchy Process

Recently, there emerge a variety of clouds in sky and thus, several similar cloud services (from different cloud venders) can be provided to a mobile end device. The goal of cloud-path selection is to find an optimal cloud-path pair between the mobile device and a cloud among a certain class of clouds that provide the same service, in order to carry out the offloaded computation tasks. It is easy to choose the optimal cloud-path to save execution time incurred by offloading program to cloud when considering only one factor. However, there are many Quality of Service (QoS)-based criteria such as performance, bandwidth, financial, security and availability that need to be considered when making final decisions. In this paper, a multiple criteria decision analysis approach based on the analytic hierarchy process (AHP) and the technique for order preference by similarity to ideal solution (TOPSIS) in a fuzzy environment is proposed to decide which cloud is the most suitable one for offloading. The AHP is used to determine the weights of the criteria for cloud-path selection, while fuzzy TOPSIS is to obtain the final ranking of alternative clouds. The numerical analysis is performed to evaluate the model. Furthermore, a method based on historical data of the mobile device’s experiences is used to evaluate the importance weights of the alternative cloud service, when it is challenge to measure and acquire the parameters of criteria timely in practical systems.

scholarly journals Differences in prioritization of the BSC’s strategic goals using AHP and ANP methods

2018 ◽  
Vol 42 (2) ◽  
pp. 193-217 ◽  
Author(s):  
Aleksander Janeš ◽  
Nina Begičević Ređep
Keyword(s):  
Decision Making ◽  
Balanced Scorecard ◽  
Analytic Network Process ◽  
Analytic Hierarchy ◽  
The Balanced Scorecard ◽  
Network Process ◽  
Strategic Goals ◽  
Key Issues ◽  
Hierarchy Process

The development and empirical verification of the balanced scorecard (BSC) model, using the multi-criteria decision-making methods (MCDM) called the analytic hierarchy process (AHP) and the analytic network process (ANP), are the key issues of the presented research. The paper presents the methodology of the prioritization of the BSC goals with the AHP and ANP methods. Even though the prioritization of the goals is possible with both, findings from the empirical analysis showed that the ANP is more complementary with the BSC because of the influences among the goals in the BSC. The ANP supports the modelling of those influences (through dependencies) and the AHP does not. The paper discusses special situations in prioritizing the BSC goals (understanding the ANP from the perspective of the user and the BSC with strategic goals that do not directly influence any other strategic goal) and proposes solutions. Therefore, it can be asserted that introducing the ANP to implement the BSC and vice versa, improved the decision-making approach and the quality of the obtained results. The research was based on a case study of modelling the BSC for Ydria Motors LL (YM), a manufacturing company.

Benchmarking of the Maintenance Service in Health Care Organizations

2017 ◽  
pp. 1-25
Author(s):  
María Carmen Carnero
Keyword(s):  
Health Care ◽  
Health Care Organizations ◽  
Health Care Organization ◽  
Care Quality ◽  
Care Staff ◽  
Care Organization ◽  
Analytic Hierarchy ◽  
Maintenance Service ◽  
Hierarchy Process

The support services of health care organizations, such as maintenance, have not traditionally been considered important from the perspective of care quality. Nevertheless, the degree of excellence in maintenance significantly influences availability, maintenance costs and safety of facilities, medical equipment, patients and care staff. Thus, it would be of great importance for health care organizations to apply benchmarking to their maintenance processes, as do other processing companies, in order to determine the quality of maintenance provided, and compare it to other, similar, organizations. This would also allow all the continuous improvement processes to be controlled, and actions for radical improvement to be carried out by comparing performance with that of companies in other sectors. This chapter describes a multicriteria model integrating a fuzzy Analytic Hierarchy Process with utility theory to obtain a valuation for the Maintenance Service of a Health Care Organization over time.

scholarly journals Modelling the Accommodation Preferences of Tourists by Combining Fuzzy-AHP and GIS Methods

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Ali Mahdi ◽  
Domokos Esztergár-Kiss
Keyword(s):  
Decision Making ◽  
Fuzzy Ahp ◽  
Security Level ◽  
Analytic Hierarchy ◽  
Gis Methods ◽  
The Cost ◽  
Hierarchy Process ◽  
Combined Technique

Finding the place of accommodation is one of the most crucial issues during a journey. This study aims to support the decision-making of tourists for choosing the optimal accommodation by combining fuzzy analytic hierarchy process (FAHP) and geographic information system (GIS) techniques. The adopted criteria are the cost per room, the distance from the center, the level of security, the place rating, and the availability of free cancellation and breakfast. Due to some uncertainty and diversity of criteria, the FAHP approach is applied to consolidate tourists’ decisions by applying criteria weighting, while the GIS is used to overlay the weighted criteria and to visualize the ranked places of accommodation on a map. The combined technique is applied on a case study in Budapest City, where the analysis is conducted on 364 places of accommodation. The results show that half of the places are recommended for tourists, and more than fifth of the accommodations are highly recommended. Furthermore, it can be concluded that the cost per room was the highest influential criterion with 0.233 importance weight, followed by the security level with 0.205. The lowest factor affecting the choice of accommodation was the free cancellation service. It was demonstrated that the rating weight importance was 0.182, while the breakfast and the distance from the center had approximately the same importance. As a recommendation, some improvements on the accommodation, such as decreasing the cost per room, enhancing the services, or developing the quality of the places, would increase their attractiveness for tourists.

A Model for Assessing the Widening of the Predictive Maintenance Strategy

2021 ◽  
pp. 213-235
Author(s):  
María Carmen Carnero ◽  
Francisco Javier Cárcel-Carrasco
Keyword(s):  
Decision Making ◽  
Predictive Maintenance ◽  
Positive Contribution ◽  
Maintenance Strategy ◽  
Analytic Hierarchy ◽  
Operational Risks ◽  
Industrial Iot ◽  
Multicriteria Model ◽  
Maintenance Schedules ◽  
Hierarchy Process

The essential aim of Industry 4.0 is to enable industries to be more productive, efficient, and flexible. A predictive maintenance strategy can make a positive contribution to all these things, as it uses industrial IoT technologies to monitor asset health, optimise maintenance schedules, provide real-time alerts about operational risks, and maximise uptime, and can provide digital services to customers based on data from its machines. It improves productivity, improves customer satisfaction, and therefore gives the company a competitive advantage. Nevertheless, decision making in relation to a predictive maintenance strategy is not systematised, and this may lead to some inappropriate decisions, which do not achieve the goal sought. This chapter describes a multicriteria model, designed with the analytic hierarchy process, to systematise decision making with respect to a predictive maintenance strategy.

On Moderate Fuzzy Analytic Hierarchy Process Pairwise Comparison Model With Subcriteria

2016 ◽  
Vol 2 (3) ◽  
pp. 54
Author(s):  
G. Marimuthu ◽  
G. Ramesh
Keyword(s):  
Decision Making ◽  
Analytic Hierarchy Process ◽  
Fuzzy Ahp ◽  
Pairwise Comparison ◽  
Decision Models ◽  
Fuzzy Analytic Hierarchy Process ◽  
Analysis Method ◽  
Analytic Hierarchy ◽  
Comparison Model ◽  
Hierarchy Process

Decisions usually involve the getting the best solution, selecting the suitable experiments, most appropriate judgments, taking the quality results etc., using some techniques.  Every decision making can be considered as the choice from the set of alternatives based on a set of criteria.  The fuzzy analytic hierarchy process is a multi-criteria decision making and is dealing with decision making problems through pairwise comparisons mode [10].  The weight vectors from this comparison model are obtained by using extent analysis method.  This paper concern with an alternate method of finding the weight vectors from the original fuzzy AHP decision model (moderate fuzzy AHP model), that has the same rank as obtained in original fuzzy AHP and ideal fuzzy AHP decision models.

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