The sugarcane supply chain is rapidly gaining attention because unstable and rising fossil fuel prices, environmental limitations, and the energy needs of growing economies in developing countries are driving demand for clean, renewable energy. Bioenergy continues to attract attention from researchers because of its various advantages over other renewable energy sources. This paper developed a mixed-integer linear programming model (MILP) to design a sustainable sugarcane-based bioenergy supply chain network to optimize a facility location and transportation flow amount for decision variables. Candidate areas will be integrated into the mathematical optimization model as candidate sugarcane fields and sugarcane factories, which consist of a sugar unit, bioethanol unit, and bioelectricity unit, will comprise the proposed supply chain design. Demand locations and amounts of sugar, bioethanol, and bioelectricity are set for each, and the supply chain is designed to satisfy or shortage those demands. Each unit has candidates and lower limits rate of capacity from which to choose appropriately and design the supply chain. The results confirm the usefulness of considering the capacity candidate in facility units. It was observed that the introduction of a lower limit capacity constraint changes the composition and costs of the supply chain.