A bi-objective robust fuzzy programming model to configure a microgrid-based cement supply chain

Designing sustainable cement supply chains presents a complex challenge due to their high energy consumption, emission intensity, and sensitivity to uncertainty. This study proposes a novel bi-objective robust fuzzy Mixed-Integer Linear Programming (MILP) model to configure a microgrid-based cement supply chain that simultaneously considers environmental and economic objectives. The proposed model incorporates local renewable energy resources through microgrids to meet the significant electrical demand of cement production, while also embedding carbon emission caps and dust emission control across the network. To handle uncertainty in demand, energy cost, and emission parameters, a robust fuzzy programming approach is adopted. The model further applies the Weighted Sum Method (WSM) to obtain Pareto-optimal solutions and support multi-criteria decision-making. A realistic illustrative case demonstrates the applicability of the model, and sensitivity analyses reveal how key parameters such as income ratio and satisfaction level serve as powerful managerial levers. The model's ability to find optimal solutions in under two seconds underscores its computational efficiency. Overall, this research fills a critical gap by offering a comprehensive, uncertainty-aware, and sustainability-driven optimization framework for cement supply chains. The proposed framework offers practical decision-making tools for supply chain managers seeking to simultaneously reduce environmental impacts and ensure economic viability.