PySensMCDA: A novel tool for sensitivity analysis in multi-criteria problems

Abstract

The presented programming package introduces an innovative tool for sensitivity analysis within Multi-Criteria Decision Analysis (MCDA), offering a modular and flexible structure for versatile applications. The PySensMCDA package is developed in Python and ensures adaptability by adjusting the behavior of sensitivity analysis methods to the specific needs of users. Robust input data validation enhances reliability by minimizing errors. The versatility of the proposed package allows for both personal and research applications within the MCDA domain, making it an important contribution to enhancing the comprehensiveness of the assessment. The eight modules encompass a variety of sensitivity analysis approaches, including alternative modification, criteria weights adjustment, probabilistic approaches, ranking alterations, compromise solutions, preference calculations, graph visualizations, and data validation. The main aim is to equip decision-makers with predefined sensitivity analysis methods, thereby facilitating more comprehensive and detailed analyses in multi-criteria decision scenarios.

Keywords

• Sensitivity analysis
• Decision-making
• Robust decisions
• Python