AGENTIC-SYSTEMSApril 14, 20261 min read11 views

Linear Programming for Multi-Criteria Assessment with Cardinal and Ordinal Data: A Pessimistic Virtual Gap Analysis

A new study introduces the Virtual Gap Analysis (VGA) method based on linear programming to address challenges in multi-criteria assessment involving both qualitative and quantitative data. This approach provides a pessimistic perspective to enhance reliability and efficiency in decision support systems.

Computer Science > Artificial Intelligence

Title:Linear Programming for Multi-Criteria Assessment with Cardinal and Ordinal Data: A Pessimistic Virtual Gap Analysis

View PDF HTML (experimental)Abstract:Multi-criteria Analysis (MCA) is used to rank alternatives based on various criteria. Key MCA methods, such as Multiple Criteria Decision Making (MCDM) methods, estimate parameters for criteria to compute the performance of each alternative. Nonetheless, subjective evaluations and biases frequently influence the reliability of results, while the diversity of data affects the precision of the parameters. The novel linear programming-based Virtual Gap Analysis (VGA) models tackle these issues. This paper outlines a two-step method that integrates two novel VGA models to assess each alternative from a pessimistic perspective, using both quantitative and qualitative criteria, and employing cardinal and ordinal data. Next, prioritize the alternatives to eliminate the least favorable one. The proposed method is dependable and scalable, enabling thorough assessments efficiently and effectively within decision support systems.

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Source: arXiv cs.AI Recent

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