This study aims to develop an integrated analytical framework for evaluating and ranking distribution centers and sales channels within a viable supply chain in the lubricant industry (case study: Behran Oil Company), with simultaneous emphasis on circular economy principles and the requirements of Industry 5.0. The research adopts a multi-criteria decision-making approach within a two-stage scenario-based model. In the first stage, evaluation criteria were identified through literature review, industrial documents, and expert opinions, and categorized into six dimensions. The criteria were then weighted using a stochastic fuzzy Best–Worst Method under three scenarios: optimistic, most likely, and pessimistic. In the second stage, distribution centers and sales channels were assessed and ranked using stochastic fuzzy TOPSIS. The results indicate that resilience is the most significant dimension, followed by sustainability and agility, while digitalization received the lowest weight. Among sub-criteria, distribution capacity flexibility and operational recovery speed were the most influential factors. The ranking results show that Center 6 achieved the highest performance, whereas Center 3 demonstrated the weakest performance. Comparative analysis with conventional methods confirmed the robustness and reliability of the proposed approach. The framework provides a practical tool for strategic decision-making at the mid-network level. The aim of this research is to provide a comprehensive analytical framework for evaluating distribution centers and sales channels in a sustainable supply chain with an emphasis on the requirements of the Fifth Industrial Revolution. This study attempts to explain, with an integrated and forward-looking perspective, the role of economic, environmental, social, resilience, agility, and digitalization criteria in the evaluation and decision-making process and provide practical insight for industrial managers and policymakers, especially in the lubricant industry. In this regard, a two-stage decision-making model has been designed and developed that systematically identifies, weights, and ultimately uses effective criteria and sub-criteria to evaluate and score distribution centers and sales channels.