Evaluating Supplier Performance Using DEA and Piecewise Triangular Fuzzy AHP

2008 ◽  
Vol 8 (3) ◽  
Author(s):  
Shouhua Yuan ◽  
Xiao Liu ◽  
Yiliu Tu ◽  
Deyi Xue
Keyword(s):  
Decision Making ◽  
Fuzzy Ahp ◽  
Pairwise Comparison ◽  
Multicriteria Decision Making ◽  
Comparison Method ◽  
Data Envelopment ◽  
Novel Method ◽  
Overall Performance ◽  
Dea Method ◽  
The Individual

Data envelopment analysis (DEA) has been widely applied in evaluating multicriteria decision making problems, which have multi-input and multi-output. However, the traditional DEA method does neither take the decision maker’s subjective preferences to the individual criteria into consideration nor rank the selected options or decision making units (DMUs). On the other hand, Satty’s analytical hierarchy process (AHP) was established to rank options or DMUs under multi-input and multi-output through pairwise comparisons. However, in most cases, the AHP pairwise comparison method is not perfectly consistent, which may give rise to confusions in determining the appropriate priorities of each criterion to be considered. The inconsistency implicates the fuzziness in generating the relative important weight for each criterion. In this paper, a novel method, which employs both DEA and AHP methods, is proposed to evaluate the overall performance of suppliers’ involvement in the production of a manufacturing company. This method has been developed through modifying the DEA method into a weighting constrained DEA method by using a piecewise triangular weighting fuzzy set, which is generated from the inconsistent AHP comparisons. A bias tolerance ratio (BTR) is introduced to represent the varying but restrained weighting values of each criterion. Accordingly, the BTR provides the decision maker a controllable parameter by tightening or loosening the range of the weighting values in evaluating the overall performance of available suppliers, which in hence, overcomes the two weaknesses of the traditional DEA method.

Evaluating Supplier Involvement Using DEA and Piecewise Triangular Fuzzy AHP

2007 ◽  
Author(s):  
Shouhua Yuan ◽  
Yiliu Tu ◽  
Deyi Xue
Keyword(s):  
Decision Making ◽  
Fuzzy Ahp ◽  
Pairwise Comparison ◽  
Comparison Method ◽  
Data Envelopment ◽  
Novel Method ◽  
Overall Performance ◽  
Dea Method ◽  
The Individual ◽  
Hierarchy Process

Data Envelopment Analysis (DEA) has been widely applied in evaluating multi-criteria decision making problems which have multi-inputs and multi-outputs. However, the traditional DEA method does neither take the decision maker’s subjective preferences to the individual criteria into consideration, nor rank the selected options or decision making units (DMUs). On the other hand, Satty’s Analytical Hierarchy Process (AHP) was established to rank options or DMUs under multi-inputs and multi-outputs through pairwise comparisons. But in most cases, the AHP pairwise comparison method is not perfectly consistent, which may give rise to confusions in determining the appropriate priorities of each criterion to be considered. The inconsistency implicates the fuzziness in generating the relative important weight for each criterion. In this paper, a novel method which employs both DEA and AHP methods is proposed to evaluate the overall performance of suppliers’ involvement in the production of a manufacturing company. This method has been developed through modifying the DEA method into a weighting constrained DEA method by using a piecewise triangular weighting fuzzy set which is generated from the inconsistent AHP comparisons. A bias tolerance ratio (BTR) is introduced to represent the varying but restrained weighting values of each criterion. Accordingly, the BTR provides the decision maker a controllable parameter by tightening or loosening the range of the weighting values in evaluating the overall performance of available suppliers, which in hence, overcomes the two weaknesses of the traditional DEA method.

scholarly journals Pairwise Comparison and Distance Measure of Hesitant Fuzzy Linguistic Term Sets

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Han-Chen Huang ◽  
Xiaojun Yang
Keyword(s):  
Decision Making ◽  
Distance Measure ◽  
Pairwise Comparison ◽  
Multicriteria Decision Making ◽  
Comparison Method ◽  
Linguistic Terms ◽  
Pairwise Comparison Matrix ◽  
Linguistic Term ◽  
Measure Methods ◽  
Fuzzy Linguistic

A hesitant fuzzy linguistic term set (HFLTS), allowing experts using several possible linguistic terms to assess a qualitative linguistic variable, is very useful to express people’s hesitancy in practical decision-making problems. Up to now, a little research has been done on the comparison and distance measure of HFLTSs. In this paper, we present a comparison method for HFLTSs based on pairwise comparisons of each linguistic term in the two HFLTSs. Then, a distance measure method based on the pairwise comparison matrix of HFLTSs is proposed, and we prove that this distance is equal to the distance of the average values of HFLTSs, which makes the distance measure much more simple. Finally, the pairwise comparison and distance measure methods are utilized to develop two multicriteria decision-making approaches under hesitant fuzzy linguistic environments. The results analysis shows that our methods in this paper are more reasonable.

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.

Pairwise Elicitation for a Decision Support Framework to Develop a Flood Risk Response Plan

2018 ◽  
Vol 5 (1) ◽  
Author(s):  
MiguelAndres Guerra ◽  
Yekenalem Abebe
Keyword(s):  
Decision Making ◽  
Flood Risk ◽  
Flood Hazard ◽  
Addis Ababa ◽  
Pairwise Comparison ◽  
Multicriteria Decision Making ◽  
Risk Response ◽  
Hazard And Risk ◽  
Response Plan ◽  
Decision Making Framework

There are several ways of quantifying flood hazard. When the scale of the analysis is large, flood hazard simulation for an entire city becomes costly and complicated. The first part of this paper proposes utilizing experience and knowledge of local experts about flood characteristics in the area in order to come up with a first-level flood hazard and risk zoning maps, by implementing overlay operations in Arc GIS. In this step, the authors use the concept of pairwise comparison to eliminate the need for carrying out a complicated simulation to quantify flood hazard and risk. The process begins with identifying the main factors that contribute to flooding in a particular area. Pairwise comparison was used to elicit knowledge from local experts and assigned weights for each factor to reflect their relative importance toward flood hazard and risk. In the second part of this paper, the authors present a decision-making framework to support a flood risk response plan. Once the highest risk zones have been identified, a city can develop a risk response plan, for which this paper presents a decision-making framework to select an effective set of alternatives. The framework integrates tools from multicriteria decision-making, charrette design process to guide the pairwise elicitation, and a cost-effective analysis to include the limited budget constraint for any city. The theoretical framework uses the city of Addis Ababa for the first part of the paper. For the second part, the paper utilizes a hypothetical case of Addis Ababa and a mock city infrastructure department to illustrate the implementation of the framework.

scholarly journals A Multicriteria Decision-Making Approach Based on Fuzzy AHP with Intuitionistic 2-Tuple Linguistic Sets

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Shahzad Faizi ◽  
Tabasam Rashid ◽  
Sohail Zafar
Keyword(s):  
Decision Making ◽  
Fuzzy Ahp ◽  
Preference Relation ◽  
Multicriteria Decision Making ◽  
Transformation Mechanism ◽  
Analytic Hierarchy ◽  
Multicriteria Decision ◽  
Linguistic Representation ◽  
Representation Model ◽  
Linguistic Preference Relation

In the modern literature related to linguistic decision-making, the 2-tuple linguistic representation model and its useful applications in various fields have been extensively studied and used during the last decade. Recently, some useful multicriteria decision-making (MCDM) methods have been introduced based on fuzzy analytic hierarchy process (AHP) for 2-tuple linguistic representation model. By keeping in mind the importance of this linguistic model, in this paper, we introduce a fuzzy AHP methodology for intuitionistic 2-tuple linguistic sets (I2TLSs) which is a useful extension of the 2-tuple linguistic representation model. This study is comprised of four stages. In the first stage, we define some operational laws for I2TL elements (I2TLEs) and prove some related important properties. In the second stage, intuitionistic 2-tuple linguistic preference relation (I2TLPR) and multiplicative I2TLPR are defined using I2TLSs. In the 3rd stage, a transformation mechanism is introduced which can transform an I2TLPR to a corresponding intuitionistic preference relation (IPR) and vice versa. In the fourth stage, an approach is proposed for checking the consistency of an I2TLPR and presented a method to repair the inconsistent one by using the proposed transformation mechanism. Finally, a numerical example is given and comparative analysis is carried out with the TOPSIS method to verify the validity of the proposed method.

scholarly journals An intelligent order allocation system for effective order fulfilment under changing customer demand

2019 ◽  
Vol 255 ◽  
pp. 02002
Author(s):  
K.H. Leung ◽  
K.L. Choy ◽  
H.Y. Lam
Keyword(s):  
Decision Making ◽  
Intelligent System ◽  
Fuzzy Ahp ◽  
Sudden Change ◽  
Pairwise Comparison ◽  
Decision Making Process ◽  
Order Allocation ◽  
Domain Experts ◽  
Customer Order ◽  
Study Results

In today's intense global competition, problems still exist under the umbrella of Just-in-Time application in the field of order management. The management of a firm usually faces difficulty in allocating stock to fulfil customer order, especially in the case of receiving a sudden change request from customers. In order to ease order allocation issues aroused by JIT, an intelligent system, namely, Intelligent Sales Order Handling System (ISOAS), is developed through the integration of fuzzy-AHP approach for decision making process in order allocation. This approach enables the selection of desired sales orders based on multiple criteria which may be quantitative or qualitative in nature, according to the judgment of scholars and domain experts. With ISOAS, customer orders are prioritized with respect to the values according to their performance under each decision making attributes. The degree of confidence of the decision judgements are quantified through the spread of fuzzy numbers with fuzzy pairwise comparison calculations. The approach can transform the fuzziness of human preference into the measurable number, enabling the operation of the AI-based system to assist humans in decision-making. An order allocation case study in a logistics department is demonstrated in this study. Results indicate an improved efficiency during the decision making process.

scholarly journals Applying Hybrid Decision-Making Method Based on Fuzzy AHP-WOWA Operator for Emergency Alternative Evaluation of Unattended Train Operation Metro System

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Bobo Zhao ◽  
Tao Tang ◽  
Bin Ning
Keyword(s):  
Decision Making ◽  
Fuzzy Ahp ◽  
Multicriteria Decision Making ◽  
Emergency Situation ◽  
Weighted Averaging ◽  
Ordered Weighted Averaging ◽  
Train Operation ◽  
Emergency Decision ◽  
Response Task ◽  
Metro System

Optimal alternative selection to address the emergency situation is critical for dispatcher group in Unattended Train Operation (UTO) to guide emergency process. It is difficult to provide the precise decision value under one criterion and to evaluate the emergency alternatives among multiple dispatchers. This paper presents a hybrid emergency decision-making method integrating fuzzy analytic hierarchy process (FAHP) described by linguistic terms with enhanced weighted ordered weighted averaging (WOWA) operator. The enhanced WOWA operator aggregates the preference matrices of multidispatcher through the constructed emergency response task model of dispatcher group in OCC. This calculation approach takes into consideration the relations of emergency tasks to derive the importance weights of dispatchers and integrates them into the ordered weighted averaging (OWA) operator weights based on a fuzzy membership relation. A case study of applying the method in an emergency of a train fire is given to demonstrate the feasibility and usefulness of the methods associated with the group multicriteria decision-making (GMCDM) theory in emergency management of UTO metro system.

On Some Advancements within Certain Multicriteria Decision Making Support Methodology

2013 ◽  
Vol 2 (2) ◽  
pp. 143 ◽  
Author(s):  
Pawel Tadeusz Kazibudzki ◽  
Andrzej Z Grzybowski
Keyword(s):  
Decision Making ◽  
Pairwise Comparison ◽  
Multicriteria Decision Making ◽  
Scientific Paper ◽  
Analytic Hierarchy ◽  
Management Activity ◽  
Multicriteria Decision ◽  
Managerial Decisions ◽  
The Right ◽  
Decision Making Support

Deriving true priority vectors from intuitive pairwise comparison matrices (PCMs) and consistency measurement of decision makers judgments about their genuine weights are crucial issues within the multicriteria decision making support methodology called Analytic Hierarchy Process (AHP). The most popular procedure in the ranking process, constitutes the Right Eigenvector Method (REV). The inventor of the AHP convinces that as long as inconsistent PCMs are allowed in the AHP none of the other existing procedures qualify and the REV provides the only right solution in this process. The objective of this scientific paper is to examine if the former opinion can be considered as experimentally confirmed. For this purpose it was decided to apply Monte Carlo methodology. However, rather than simulate and analyze simulations results for a single PCM, as it has been done so far by many other authors, we decided to design and analyze computer simulations results for a singular model of the AHP framework. Our findings lead to inevitable conclusion that the REV cannot longer be perceived as a dominant procedure within the AHP methodology, especially when nonreciprocal PCMs are considered. It was verified empirically in our research that in the situation when nonreciprocal PCMs are considered the REV impoverishes the entire AHP methodology by its lack of PCMs inconsistency measure in such cases. Moreover, it provides less accurate rankings for a particular decision in comparison to other presented methods. It was also unequivocally verified that the enforced reciprocity of PCM leads directly to worse estimates of priorities weights. Altogether, it seems very important from the perspective of methodology supporting multicriteria decision making, the crucial process embedded in most of management activity. In the consequence, because the REV recedes other prioritization procedures available for the AHP methodology, it is advised to consider them instead, especially under some circumstances of an important and very tight managerial decisions.

scholarly journals Hesitant Fuzzy Linguistic Multicriteria Decision-Making Method Based on Generalized Prioritized Aggregation Operator

2014 ◽  
Vol 2014 ◽  
pp. 1-16 ◽  
Author(s):  
Jia-ting Wu ◽  
Jian-qiang Wang ◽  
Jing Wang ◽  
Hong-yu Zhang ◽  
Xiao-hong Chen
Keyword(s):  
Decision Making ◽  
Multicriteria Decision Making ◽  
Comparison Method ◽  
Aggregation Operator ◽  
New Approach ◽  
Multicriteria Decision ◽  
Scale Functions ◽  
Prioritized Aggregation Operator ◽  
Prioritized Aggregation Operators ◽  
Fuzzy Linguistic

Based on linguistic term sets and hesitant fuzzy sets, the concept of hesitant fuzzy linguistic sets was introduced. The focus of this paper is the multicriteria decision-making (MCDM) problems in which the criteria are in different priority levels and the criteria values take the form of hesitant fuzzy linguistic numbers (HFLNs). A new approach to solving these problems is proposed, which is based on the generalized prioritized aggregation operator of HFLNs. Firstly, the new operations and comparison method for HFLNs are provided and some linguistic scale functions are applied. Subsequently, two prioritized aggregation operators and a generalized prioritized aggregation operator of HFLNs are developed and applied to MCDM problems. Finally, an illustrative example is given to illustrate the effectiveness and feasibility of the proposed method, which are then compared to the existing approach.

scholarly journals Hesitant Fuzzy-Stochastic Data Envelopment Analysis (HF-SDEA) Model for Benchmarking

2021 ◽  
Vol 5 (1) ◽  
pp. 94
Author(s):  
Dahlan Abdullah ◽  
Hartono ◽  
Cut Ita Erliana
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Fuzzy Model ◽  
Assessment Process ◽  
Data Envelopment ◽  
Dynamic Data ◽  
Decision Making Unit ◽  
Dynamic Data Envelopment Analysis ◽  
Dea Method ◽  
Stochastic Data

The Data Envelopment Analysis (DEA) method is a method commonly used in benchmarking. The Dynamic Data Envelopment Analysis (DDEA) method was proposed to improve the DEA method in the benchmarking process. The DDEA method proposed can determine the effectiveness of the Decision Making Unit (DMU). The disadvantage of the DDEA model is that it cannot handle problems that involve benchmarking for stochastic data. To improve the DDEA method, the Stochastic Data Envelopment Analysis (SDEA) method is proposed which can be used for benchmarking involving stochastic data. The SDEA method itself has weaknesses in dealing with noise and uncertainty problems that will appear in the assessment process. The purpose of the research conducted by the researcher was to use the Hesitant Fuzzy method in optimizing the SDEA method so that the Hesitant Fuzzy model - Stochastic Data Envelopment Analysis (HF-SDEA) could be carried out benchmarking process in a situation where the assessment contained many elements of uncertainty. The results of this study are benchmarking methods that can do benchmarking for stochastic data on conditions that contain elements of uncertainty.

Sign in / Sign up

Export Citation Format

Share Document