Integrating fuzzy analytical hierarchy process and data envelopment analysis for performance management in automobile repair shops

2009 ◽  
Vol 3 (4) ◽  
pp. 450 ◽  
Author(s):  
R. Parameshwaran ◽  
P.S.S. Srinivasan ◽  
M. Punniyamoorthy ◽  
S.T. Charunyanath ◽  
C. Ashwin
Author(s):  
NORITA AHMAD ◽  
DANIEL BERG ◽  
GENE R. SIMONS

This research focuses on developing a model that can be used to assess the performance of Small to Medium-Sized Manufacturing Enterprises (SMEs). The model will result from the integration of a decision tool called the Analytical Hierarchy Process (AHP) and a data analysis model called Data Envelopment Analysis (DEA). This research demonstrates that by eliminating flaws and taking advantage of each methodology's specific characteristics in identifying and solving problems, the new integrated AHP/DEA model appears to be a logical and sensible solution in multi-criteria decision-making problem.


2014 ◽  
Vol 687-691 ◽  
pp. 1560-1563
Author(s):  
Han Cong Tang ◽  
Yan An Dong

This paper presents three models as a potential decision making method for selecting the best baseball, field hockey, and women’s basketball NCAA Division I coaches. Five indicators, synthesized coaching efficiency, winning percentage, consecutive championship, achievement index and gender, are introduced to give a comprehensive evaluation of coaching ability. The preliminary served as a filter model to screen out less capable coaches and a robust ranking within top 10 is achieved. The Data Envelopment Analysis (DEA) model takes the time line horizon into consideration, and helps find less efficient coaches. By comparing the first two models, we obtain a reasonable assessment of coaches from different time period. Finally, by applying the Analytical Hierarchy Process (AHP), minor changes in judgment matrices can be made to adjust the ratio of male to female in the top 5 coaches.


Processes ◽  
2019 ◽  
Vol 7 (8) ◽  
pp. 494 ◽  
Author(s):  
Xu ◽  
Wang ◽  
Shah ◽  
Zameer ◽  
Solangi ◽  
...  

The widespread penetration of hydrogen in mainstream energy systems requires hydrogen production processes to be economically competent and environmentally efficient. Hydrogen, if produced efficiently, can play a pivotal role in decarbonizing the global energy systems. Therefore, this study develops a framework which evaluates hydrogen production processes and quantifies deficiencies for improvement. The framework integrates slack-based data envelopment analysis (DEA), with fuzzy analytical hierarchy process (FAHP) and fuzzy technique for order of preference by similarity to ideal solution (FTOPSIS). The proposed framework is applied to prioritize the most efficient and sustainable hydrogen production in Pakistan. Eleven hydrogen production alternatives were analyzed under five criteria, including capital cost, feedstock cost, O&M cost, hydrogen production, and CO2 emission. FAHP obtained the initial weights of criteria while FTOPSIS determined the ultimate weights of criteria for each alternative. Finally, slack-based DEA computed the efficiency of alternatives. Among the 11, three alternatives (wind electrolysis, PV electrolysis, and biomass gasification) were found to be fully efficient and therefore can be considered as sustainable options for hydrogen production in Pakistan. The rest of the eight alternatives achieved poor efficiency scores and thus are not recommended.


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