Study cases
The development of a suite of tools is very important but it is not enough if users cannot use it to verify its performance with real datasets in order to make comparisons with either their own proposals or problems. In this section, you can find a repository of case studies and datasets for different decision making problems with linguistic and complex frameworks that can be solved by using FLINTSTONES.
Each case study is associated with its datasets for FLINTSTONES that includes the definition of the evaluation framework and the set of assessments provided by experts. Furthermore, each case study is associated with the research paper in which the use of the 2-tuple linguistic representation model or any of its extensions has been applied to it successfully. The repository is not closed, it is open to increase in a future.
The case studies of the repository are categorized by the type of complex framework
- Multi-granular linguistic framework
- Heterogeneous framework
- Unbalanced linguistic framework
- BETA! Hesitant Fuzzy Linguistic Term Set
Due to the fact that the results shown in each the research paper were calculated manually or through software tools in beta version, sometimes, there are slight variations in the results shown in the associated papers and the results provided by the FLINTSTONES software tool. Therefore, the valid results of the datasets are generated by the FLINTSTONES software tool.
Multi-granular context
QoS Services
- Associated Paper: S. Gramajo, L. Martínez, A Linguistic Decision Support Model for QoS Priorities in Networking. Knowledge-based Systems, vol. 32, issue 1, pp. 65-75, 2012.
- DataSet File
- Features Dataset:
- Multi-Experts: 7 experts
- Single-Criteria: priorization
- Alternatives: 10 QoS services
- Expression Domain: Multiple linguistic scales
- Linguistic scale with 9 labels
- Linguistic scale with 7 labels
- Linguistic scale with 5 labels
Investment company - Flexible Framework
- Associated Paper: M. Espinilla, J. Liu, L. Martínez, An Extended Hierarchical Linguistic Model for Decision-Making Problems. Computational Intelligence, vol. 27, issue 3, pp. 489-512, 2011.
- DataSet File
- Features Dataset:
- Multi-Experts: 4 experts
- Single-Criteria: preference
- Alternatives: 4 alternatives
- Expression Domain: Multiple linguistic scales
- Linguistic scale with 3 labels
- Linguistic scale with 5 labels
- Linguistic scale with 7 labels
Investment company
- Associated Paper:F. Herrera, L. Martínez, A model based on linguistic 2-tuples for dealing with multigranularity hierarchical linguistic contexts in Multiexpert Decision-Making. IEEE Transactions on Systems, Man and Cybernetics. Part B: Cybernetics, vol. 31, issue 2, pp. 227-234, 2001.
- DataSet File
- Features Dataset:
- Multi-Experts: 4 experts
- Single-Criteria: preference
- Alternatives: 4 alternatives
- Expression Domain: Multiple linguistic scales
- Linguistic scale with 3 labels
- Linguistic scale with 5 labels
- Linguistic scale with 9 labels
Olive Oil Sensory Evaluation
- Associated Paper:L. Martínez, M. Espinilla, L.G. Pérez, A Linguistic Multigranular Sensory Evaluation Model for Olive Oil. International Journal of Computational Intelligence Systems, vol. 1, issue 2, pp. 148-158, 2008.
- DataSet File
- Features Dataset:
- Multi-Experts: 8 tasters
- Multi-Criteria: 9 sensory features
- Alternatives: 1 olive oil sample
- Expression Domain: Multiple linguistic scales
- Linguistic scale with 5 labels
- Linguistic scale with 9 labels
Heterogeneous contexts
360-degree performance appraisal
- Associated Paper: M. Espinilla, R. de Andrés, F.J. Martínez, L. Martínez, A 360-degree performance appraisal model dealing with heterogeneous information and dependent criteria. Information Sciences, vol. 222, pp. 459-471, 2013.
- DataSet File
- Features Dataset:
- Multi-Experts: 3 collectives
- Supervisors (1 area manager, 3 direct supervisors, 3 non-direct supervisors)
- Collaborators (7 selling employees and 4 non-selling employees)
- Customers (20 customers)
- Multi-Criteria: 11 criteria
- Cost: 3 criteria
- Benefit: 8 criteria
- Alternatives: 7 evaluated employees
- Expression Domain: Heterogeneous information
- Numeric
- Linguistic scale with 3 labels
- Linguistic scale with 5 labels
- Linguistic scale with 7 labels
- Linguistic scale with 9 labels
- Multi-Experts: 3 collectives
Sustainable energy evaluation
- Associated Paper: M. Espinilla, I. Palomares, L. Martínez, D. Ruan, A comparative study of heterogeneous decision analysis approaches applied to sustainable energy evaluation.International Journal on Uncertainty, Fuzziness and Knowledge-based Systems, vol. 20, issue supp01, pp. 159-174, 2012.
- DataSet File
- Features Dataset:
- Multi-Experts: 6 experts
- Multi-Criteria: 15 criteria
- Alternatives: 3 energy policies
- Expression Domain: Heterogeneous information
- Numeric
- Interval
- Linguistic scale with 5 labels
ERP system evaluation
- Associated Paper: P.J. Sánchez, L. Martínez, C. García, F. Herrera, E. Herrera-Viedma, A Fuzzy Model to Evaluate the Suitability of Installing an ERP System.Information Sciences, vol. 179, issue 14, pp. 2333-2341, 2009.
- DataSet File
- Features Dataset:
- Multi-Experts: 4 experts
- Single-Criteria: 1 criterion
- Alternatives: 9 alternatives
- Expression Domain: Heterogeneous information
- Numeric
- Interval
- Linguistic scale with 5 labels
- Linguistic scale with 7 labels
- Linguistic scale with 9 labels
Unbalanced linguistic context
Grading systems
- Associated Paper: F. Herrera, E. Herrera-Viedma, L. Martínez, A Fuzzy Linguistic Methodology To Deal With Unbalanced Linguistic Term Sets. IEEE Transactions on Fuzzy Systems, vol. 16, issue 2, pp. 354-370, 2008.
- DataSet File
- Features Dataset:
- Single-Expert: 1 Teacher
- Multi-Criteria: 7 Subjects
- Alternatives: 2 Students
- Expression Domain: Unbalanced linguistic scale with 5 labels
- Left side: 1 label
- Center: 1 label
- Right side: 3 labels with extreme density
Olive Oil Sensory Evaluation. Unbalanced Linguistic Scale
- Associated Paper:L. Martínez, M. Espinilla, J. Liu, L.G. Pérez, P.J. Sánchez, An Evaluation Model with Unbalanced Linguistic Information:Applied to Olive Oil Sensory Evaluation. Journal of Multiple-Valued Logic and Soft Computing, vol. 15, issue 2, pp. 229-251, 2009.
- DataSet File
- Features Dataset:
- Multi-Experts: 8 tasters
- Multi-Criteria: 9 sensory features
- Alternatives: 1 olive oil sample
- Expression Domain: Unbalanced linguistic scale with 5 labels
- Left side: 3 labels with extreme density
- Center: 1 label
- Right side: 1 label
Hesitant Fuzzy Linguistic Term Set
Manager of garment company. Hesitant Fuzzy Linguistic Term Set
- Paper is submitted to FUZZ-IEEE 2014:Francisco J. Estrella, Rosa M. Rodriguez, Macarena Espinilla and Luis Martinez. On the use of Hesitant Fuzzy Linguistic Term Set in FLINTSTONES.
- DataSet File
- Features Dataset:
- Experts: 1 expert
- Multi-Criteria: 3 criteria
- Alternatives: 3 alternatives
- Expression Domain: Hesitant Fuzzy Linguistic Term Sets.
ELICIT Expressions
PhD student selection
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Paper is submitted to the journal IEEE Transactions on Fuzzy Systems: Álvaro Labella, Rosa M. Rodríguez and Luis Martínez. Computing with Comparative Linguistic Expressions and Symbolic Translation for Decision Making: ELICIT Information.
- Features Dataset:
- Experts: 3 expert
- Multi-Criteria: 3 criteria
- Alternatives: 4 alternatives
- Expression Domain: Hesitant Fuzzy Linguistic Term Sets.
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