Version [1.4]- [pymcdm – The universal library for solving multi-criteria decision-making problems]

In this work, we present a new update of the pymcdm library that substantially expands its methodological scope and analytical capabilities for Multi-Criteria Decision-Making (MCDM) research. The update introduces several recently developed MCDM methods and one objective weighting method, all accompanied by documentation and comprehensive tests based on the literature. Enhancements to existing methods include support for gray-code ordering in the Characteristic Objects method (COMET) and the addition of a weighted ESP expert model for expert-based evaluations. To facilitate methodological analysis and comparative studies, a new utility function has been implemented for systematic parameter exploration. Furthermore, the library now provides a dedicated distance module offering ranking comparison metrics, such as Kemeny, Frobenius, and DraWS distances. This update also improves numerical stability through fixes in normalization procedures, refines correlation measures and validation utilities, and delivers extensive documentation updates.