Extensions of the TOPSIS for group decision-making under fuzzy environment
Fuzzy Sets and Systems
An approach to avoiding rank reversal in AHP
Decision Support Systems
Weapon selection using the AHP and TOPSIS methods under fuzzy environment
Expert Systems with Applications: An International Journal
A fuzzy extension of Saaty's priority theory
Fuzzy Sets and Systems
Project selection for oil-fields development by using the AHP and fuzzy TOPSIS methods
Expert Systems with Applications: An International Journal
A performance evaluation model by integrating fuzzy AHP and fuzzy TOPSIS methods
Expert Systems with Applications: An International Journal
Application of Interval-Valued AHP and Fuzzy TOPSIS in the Quality Classification of the Heaters
CIMSIM '10 Proceedings of the 2010 Second International Conference on Computational Intelligence, Modelling and Simulation
Expert Systems with Applications: An International Journal
Multicriteria decision making in energy planning using a modified fuzzy TOPSIS methodology
Expert Systems with Applications: An International Journal
A Delphi-AHP-TOPSIS based benchmarking framework for performance improvement of a cold chain
Expert Systems with Applications: An International Journal
Fuzzy failure modes and effects analysis by using fuzzy TOPSIS-based fuzzy AHP
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
On rank reversal in decision analysis
Mathematical and Computer Modelling: An International Journal
Combining grey relation and TOPSIS concepts for selecting an expatriate host country
Mathematical and Computer Modelling: An International Journal
Hi-index | 12.05 |
The acquisition of custom design equipment may be accomplished by selecting a supplier to launch a product development project. That selection is usually performed by a bidding process that requires a procedure for the evaluation of proposals. This paper proposes a modification to a method for multi-criteria decision analysis as a support in evaluation. The method, originally implemented by several authors, is based on a combination of fuzzy Analytic Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS). The proposed modifications permit the direct entry of data to three types of parameters (numerical parameters, binary descriptors and linguistic variables). The calculation of weights for each evaluation criterion is performed by a new approach to fuzzy AHP that facilitates the assessment and permits the simultaneous verification of consistency. The proposed improved method includes a procedure for the detection and analysis of possible problems of rank reversal. A numerical example is presented using data from an actual case of a request for proposals for the supply of customized lottery ticket printers.