On ordered weighted averaging aggregation operators in multicriteria decisionmaking
IEEE Transactions on Systems, Man and Cybernetics
Fuzzy Sets and Systems
Fuzzy efficiency measures in data envelopment analysis
Fuzzy Sets and Systems
Fuzzy DEA: a perceptual evalution method
Fuzzy Sets and Systems
Idea and Ar-Idea: Models for Dealing with Imprecise Data in Dea
Management Science
Toward a generalized theory of uncertainty (GTU): an outline
Information Sciences—Informatics and Computer Science: An International Journal
A method for fuzzy aggregation based on group expert evaluations
Fuzzy Sets and Systems
Interval efficiency assessment using data envelopment analysis
Fuzzy Sets and Systems
Information Sciences: an International Journal
Self-organizing fuzzy aggregation models to rank the objects with multiple attributes
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
A robust optimization approach for imprecise data envelopment analysis
Computers and Industrial Engineering
An ideal-seeking fuzzy data envelopment analysis framework
Applied Soft Computing
Fuzzy clustering algorithms for unsupervised change detection in remote sensing images
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
Efficiencies of two-stage systems with fuzzy data
Fuzzy Sets and Systems
Efficiency of parallel production systems with fuzzy data
Fuzzy Sets and Systems
Computers and Industrial Engineering
Expert Systems with Applications: An International Journal
| Hi-index | 0.08 |
In this paper, fuzzy DEA (data envelopment analysis) models are proposed for evaluating the efficiencies of objects with fuzzy input and output data. The obtained efficiencies are also fuzzy numbers that reflect the inherent ambiguity in evaluation problems under uncertainty. An aggregation model for integrating fuzzy attribute values is provided in order to rank objects objectively. Using the proposed method, a case study involving a restaurant location problem is analyzed in detail. Rent of establishment, traffic amount, level of security, consumer consumption level and competition level are identified as the primary factors in determining an ideal location for a Japanese-style rotisserie restaurant. Based on field investigation, the uncertain information on primary factors is represented by fuzzy numbers. Using the fuzzy aggregation model, the best location of restaurant is determined. The case study shows that fuzzy DEA models can be quite useful for solving business problems under uncertainty.