DEVELOPMENT OF AN OPTIMIZED HYBRID MULTI-CRITERIA DECISION-MAKING ALGORITHM FOR COMPLEX SOCIO-ECONOMIC SYSTEMS

This paper presents an advanced hybrid multi-criteria decision-making (MCDM) framework designed to optimize strategic planning within complex socio-economic environments. Building upon foundational algorithms previously evaluated in high-dimensional settings, this study introduces a dynamic weight-tuning constraint satisfaction matrix. The proposed system mitigates the inherent instability of traditional empirical scoring methods by embedding real-time feedback loops. Experimental results demonstrate a 14.2% increase in computational efficiency and a significant reduction in convergence errors compared to baseline models.