IMAT Method Supporting Data: Multi-Criteria Decision-Making Case Studies

Supporting data for the IMAT multi-criteria decision-making method includes four Excel files. The first dataset contains case studies for air transportation company selection and aerial target threat assessment. Three additional datasets are filtered selections from the UCI Machine Learning Repository, each annotated with aspiration levels for radical, compromise, and conservative decision-makers.

Use Cases

• Benchmarking multi-criteria decision-making algorithms based on the provided aspiration levels for different decision-maker types.
• Evaluating company selection methods using the air transportation case study data.
• Assessing threat assessment models using the aerial target case study data.
• Conducting comparative experiments on decision-making styles using the three annotated UCI datasets.

Strengths

• Data is structured for specific case studies in air transportation and threat assessment.
• Includes three additional datasets from the UCI Machine Learning Repository for expanded experimentation.
• Released under a permissive CC-BY-4.0 license for reuse.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The description metadata is limited; actual data quality requires manual inspection.

Provenance

Source

Author Lisha Peng; first dataset created for case studies, others filtered from UCI Machine Learning Repository.

Collection Method

Likely compiled for research on the IMAT decision-making method.

Freshness

Last updated 2026-05-07 10:24:20; freshness should be verified.