Vendors selection VIA a spreadsheet analytical hierarchy process
Proceedings of the 15th annual conference on Computers and industrial engineering
A fuzzy goal programming approach for vendor selection problem in a supply chain
Computers and Industrial Engineering
Proceedings of the 35th conference on Winter simulation: driving innovation
Research on Vendor Selection under Fuzzy Situation
AMS '08 Proceedings of the 2008 Second Asia International Conference on Modelling & Simulation (AMS)
Information Sciences: an International Journal
A fuzzy supplier selection model with the consideration of benefits, opportunities, costs and risks
Expert Systems with Applications: An International Journal
An integrated fuzzy model for supplier management: A case study of ISP selection and evaluation
Expert Systems with Applications: An International Journal
Supplier selection: A hybrid model using DEA, decision tree and neural network
Expert Systems with Applications: An International Journal
An novel approach to supplier selection based on vague sets group decision
Expert Systems with Applications: An International Journal
An integrated fuzzy-lp approach for a supplier selection problem in supply chain management
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Application of decision-making techniques in supplier selection: A systematic review of literature
Expert Systems with Applications: An International Journal
Integration of semi-fuzzy SVDD and CC-Rule method for supplier selection
Expert Systems with Applications: An International Journal
Hi-index | 12.06 |
This study consists of three types of vendor selection models in supply chains and presents a decision making scheme for choosing appropriate method for supplier selection under certainty, uncertainty and probabilistic conditions. These models are, Data Envelopment Analysis (DEA), Fuzzy Data Envelopment Analysis (FDEA), and Chance Constraint Data Envelopment Analysis (CCDEA). In FDEA model we use @a-cut method in five levels for @a, to convert fuzzy DEA into interval programming. Also, we solve the CCDEA model for two levels of probabilities. It is assumed that inputs are random variables. Under this assumption the efficiency scores of Decision Making Units (DMUs) are random variables. Obtained results form each model is: average efficiency scores of DMUs, variance of efficiency scores, and 95% confidence interval for average. Results from three models are compared. Our decision making scheme allows decision makers to perform analysis among input factors which are expected costs, quality of acceptance levels, and on-time delivery. This is the first study to a present a flexible approach for supply chain risk and vendor selection. The superiority of the flexible algorithm is shown for 10 suppliers. Its features are also compared with previous models to show its advantages over previous models.