Fuzzy sets, decision making and expert systems
Fuzzy sets, decision making and expert systems
Selection of vendors—a mixed-integer programming approach
CIE '96 Proceedings of the 19th international conference on Computers and industrial engineering
A fuzzy approach to the multiobjective transportation problem
Computers and Operations Research
A fuzzy goal programming approach for vendor selection problem in a supply chain
Computers and Industrial Engineering
A hybrid approach to supplier selection for the maintenance of a competitive supply chain
Expert Systems with Applications: An International Journal
Supplier selection with an integrated methodology in unknown environment
Expert Systems with Applications: An International Journal
Selection of new production facilities with the Group Analytic Hierarchy Process Ordering method
Expert Systems with Applications: An International Journal
Fuzzy AHP approach for supplier selection in a washing machine company
Expert Systems with Applications: An International Journal
A multi-objective decision making model for the vendor selection problem in a bifuzzy environment
Expert Systems with Applications: An International Journal
A fuzzy decision support system for digital camera selection based on user preferences
Expert Systems with Applications: An International Journal
A fuzzy-Bayesian model for supplier selection
Expert Systems with Applications: An International Journal
A fuzzy solution approach for multi objective supplier selection
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
Hi-index | 12.06 |
Traditionally, supplier selection should simultaneously take into account numerous heterogeneous criteria, and then is a tedious task for the purchasing decision makers. It becomes especially complicated when quantity discounts are considered at the same time. Under such manner, most studies often formulate such a problem as a Multi-Objective Linear Programming (MOLP) problem, and then scale it down to a Mixed Integer Programming (MIP) problem to handle the inherited multi-objectives simultaneously. However, this approach often neglects to consider scaling and subjective weighting issues. In order to ease the problem mentioned above and to obtain a more reasonable compromise solution for allocating order quantities among suppliers with their quantity discount rate offered, the Analytical Hierarchy Process (AHP) and fuzzy compromise programming are introduced in this study. An illustrated example is presented to demonstrate the proposed model and to illuminate two kinds of attitudes for decision makers. The information from the experiments can be utilized further to explain the suppliers' possible improvement and to help create win-win policies.