<p>This study introduces a robust multi-criteria optimization framework for supplier selection, integrating cost, delivery time, and advanced innovation sub-criteria to achieve balanced, strategic, and sustainable allocations. The framework ensures that supplier allocations align with long-term organizational goals, prioritizing innovation and delivery performance while maintaining cost efficiency. High-innovation suppliers are effectively rewarded, and delivery performance alignment is enhanced, demonstrating the framework’s ability to address critical strategic dimensions of supply chain management. The proposed approach mitigates risks by promoting resilience, competitiveness, and adaptability in dynamic supply chain environments. Using stochastic modeling and machine learning techniques for weight determination, the model captures the complexities of modern supply chains, ensuring comprehensive and data-driven decision-making. This research underscores the importance of multi-criteria decision-making in building sustainable and innovation-driven supply chains, balancing short-term operational efficiency with long-term strategic objectives.</p>