An Application of Fuzzy Data Envelopment Analytical Hierarchy Process for Reducing Defects in the Production of Liquid Medicine

2010 ◽  
Vol 9 (3) ◽  
pp. 251-261 ◽  
Author(s):  
Suphattra Ketsarapong ◽  
Varathorn Punyangarm
Keyword(s):  
Analytical Hierarchy Process ◽  
Data Envelopment ◽  
Fuzzy Data ◽  
Hierarchy Process ◽  
Liquid Medicine

THE INTEGRATION OF ANALYTICAL HIERARCHY PROCESS AND DATA ENVELOPMENT ANALYSIS IN A MULTI-CRITERIA DECISION-MAKING PROBLEM

2006 ◽  
Vol 05 (02) ◽  
pp. 263-276 ◽  
Author(s):  
NORITA AHMAD ◽  
DANIEL BERG ◽  
GENE R. SIMONS
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Analytical Hierarchy Process ◽  
Data Envelopment ◽  
Multi Criteria Decision Making ◽  
Analysis Model ◽  
Decision Tool ◽  
Manufacturing Enterprises ◽  
Decision Making Problem ◽  
Hierarchy Process

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.

Assessment of Coaches Using Data Envelopment Analysis and Analytical Hierarchy Process

2014 ◽  
Vol 687-691 ◽  
pp. 1560-1563
Author(s):  
Han Cong Tang ◽  
Yan An Dong
Keyword(s):  
Data Envelopment Analysis ◽  
Analytical Hierarchy Process ◽  
Comprehensive Evaluation ◽  
Data Envelopment ◽  
Filter Model ◽  
Winning Percentage ◽  
Evaluation Of Coaching ◽  
And Gender ◽  
Using Data ◽  
Hierarchy Process

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.

A Hybrid Portfolio Selection Model

2020 ◽  
Vol 16 (3) ◽  
pp. 100-116
Author(s):  
Praveen Ranjan Srivastava ◽  
Prajwal Eachempati
Keyword(s):  
Analytical Hierarchy Process ◽  
Credit Rating ◽  
Fuzzy Topsis ◽  
Data Envelopment ◽  
Criteria Weights ◽  
Indian Stock Market ◽  
Hierarchy Process ◽  
Asset Managers ◽  
Portfolio Selection Model ◽  
Rating Information

It is generally observed that investors approach asset managers and financial analysts to recommend a customized portfolio based on certain personalized preferences. The article discusses a methodology to build a hybrid personalized multi-criteria model in the Indian stock market context suiting investor preferences. The analytical hierarchy process (AHP) was used to compute the criteria weights and data envelopment analysis (DEA) was adopted to screen the best portfolios which were subsequently ranked by a fuzzy technique for order of preference by similarity to ideal solution (FTOPSIS) and evaluation based on distance from average solution (EDA). The rankings of portfolios were validated for robustness with the actual rankings awarded by Credit Rating Information Services of India Limited (CRISIL) to demonstrate the efficacy of the hybrid model and it was found that Fuzzy TOPSIS and EDA rankings were consistent with the CRISIL rankings proposed by expert investors.

An application of hybrid data envelopment analytical hierarchy process approach for supplier selection

2015 ◽  
Vol 28 (2) ◽  
pp. 218-242 ◽  
Author(s):  
Vinod Yadav ◽  
Milind Kumar Sharma
Keyword(s):  
Analytical Hierarchy Process ◽  
Supplier Selection ◽  
Selection Process ◽  
Selection Problem ◽  
Data Envelopment ◽  
Content Type ◽  
Hybrid Data ◽  
Hierarchy Process ◽  
A Company ◽  
Supplier Selection Problem

Purpose – The problem of supplier selection gets complicated when a company looks for various criteria to evaluate different suppliers. The decision criteria used for supplier selection process can be different for different organizations due to a large number of factors. Hence, it can be said that supplier selection is basically, a multiple criteria decision-making (MCDM) problem. The purpose of this paper is to propose a hybrid data envelopment analytical hierarchy process (DEAHP) approach to solve the supplier selection problem for an automobile company. Design/methodology/approach – In this study, the data envelopment analysis (DEA) approach is embedded into analytic hierarchy process (AHP) methodology. Literature review suggested that majority of researches found it appropriate using DEA and AHP methodologies for supplier selection process; hence it is felt that a hybrid DEAHP would be a useful methodology to offer a MCDM model for supplier selection problem. Findings – First, the key criteria of the supplier selection problem for the company are identified. Then a model is developed and implemented for supplier selection using DEAHP approach. This study concluded that quality, cost and service are the most crucial criteria for an automobile company operational in a developing country like India. Sensitivity analysis further helped to evaluate suppliers based on each criterion. Research limitations/implications – As this analysis and findings are based on only one case study of an Indian automobile company, and this necessitates caution in interpreting the results. The limited number of interviewed managers in a company restricts the generalizability of the results. Though the company selected for this study is typical of developing country businesses, the findings of the paper may not be readily extensible to other companies. Second, this study used retrospective settings, based on the interviewed feedback after the events had occurred. This method naturally poses limitations due to respondent recall and the accuracy of information provided. Third, the problem chosen for this study is based in a single country context and further additional research will be required to examine if the findings could be extended to other automobile companies in other developing nations. Also in some cases technique used in the study may pose some extra computational efforts. Practical implications – This study points out the importance of the supplier selection problem. It provides key criteria for supplier selection in Indian context also proposes a framework to deal with multiple criteria. proposed model deals with two crucial criteria long term relationships and flexibility which were relatively less discussed and considered in the literature in past. Originality/value – The proposed MCDM model can provide the guidelines and directions for the decision makers to effectively choose suppliers in the current competitive environment.

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