Software Reliability as User Perception: Application of the Fuzzy Analytic Hierarchy Process to Software Reliability Analysis

2017 ◽  
Author(s):  
Felipe Febrero ◽  
M. Angeles Moraga ◽  
Coral Calero
Keyword(s):  
Analytic Hierarchy Process ◽  
Reliability Analysis ◽  
Software Reliability ◽  
Fuzzy Analytic Hierarchy Process ◽  
User Perception ◽  
Analytic Hierarchy ◽  
Hierarchy Process

scholarly journals Facility Layout Planning with SHELL and Fuzzy AHP Method Based on Human Reliability for Operating Theatre

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
QingLian Lin ◽  
Duojin Wang
Keyword(s):  
Analytic Hierarchy Process ◽  
Reliability Analysis ◽  
Fuzzy Ahp ◽  
Facility Layout ◽  
Operating Theatre ◽  
Fuzzy Analytic Hierarchy Process ◽  
Human Reliability ◽  
Analytic Hierarchy ◽  
Layout Planning ◽  
Hierarchy Process

A well-design facility layout planning refers to the reduction of the operation cost in the manufacturing and service industry. This work consists of reliability analysis of facility layout for an operating theatre; it aims at proposing a new evaluation approach, which integrated the fuzzy analytic hierarchy process and human reliability tool, for optimization of facility layout design with safety and human factors in an operating theatre. Firstly, the systematic layout planning is used to design the layout schemes on the basis of field investigations. Then, the criteria system is proposed based on human reliability analysis from four perspectives: software, hardware, environment, and liveware. Finally, the fuzzy analytic hierarchy process, a fuzzy extension of the multicriteria decision-making technique analytic hierarchy process, is used to compare these layout schemes based on the criteria system. The results that are obtained reveal interesting properties of facility layout planning in hospitals. It reveals that decision in selecting a suitable layout must meet not only the strategies and goals of the system but also meet the safety, security, and reliability of the system.

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.

scholarly journals Research on Knowledge Management Models at Universities Using Fuzzy Analytic Hierarchy Process (FAHP)

2021 ◽  
Vol 13 (2) ◽  
pp. 809
Author(s):  
Ngoc Thach Pham ◽  
Anh Duc Do ◽  
Quang Vinh Nguyen ◽  
Van Loi Ta ◽  
Thi Thanh Binh Dao ◽  
...  
Keyword(s):  
Knowledge Management ◽  
Analytic Hierarchy Process ◽  
Fuzzy Analytic Hierarchy Process ◽  
Data Systems ◽  
Knowledge Use ◽  
Analytic Hierarchy ◽  
Priority Order ◽  
Big Data Systems ◽  
Document Review ◽  
Hierarchy Process

This study aims to investigate and evaluate factors related to the knowledge management model at universities in Hanoi, Vietnam. Based on the system literature review (SLR) approach, the study follows descriptive and inductive approach results of the document review process. Eight factors were synthesized with the fuzzy analytic hierarchy process (FAHP) to evaluate the priority order. Ten experts from seven universities participated in the survey. The results rank as follows: (1) knowledge sharing factor (this also has the highest best nonfuzzy performance (BNP) and average multiplier weight (GM)); (2) knowledge management with big data systems; (3) knowledge creation; (4) knowledge use; (5) knowledge gathering; (6) leadership; (7) knowledge rating; and (8) knowledge storage. Discussions, conclusions, limitations of the study, and suggestions for future studies are also mentioned in this study.

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