In this chapter, we present a mathematical framework to model and optimize a supply chain for industrial chemical products derived from biomass. A multi-objective, multi-period mixed-integer linear programming (MILP) model that takes various aspects of the supply chain into account is designed and implemented. Important decisions include the location, capacity and technology selection for the refineries, selection of suppliers and customers, production planning, transportation scheduling as well as inventory management. Seasonality in biomass supply and degradation of biomass are both captured in the model. The proposed multi-objective MILP model is solved using the ε-constraint method to simultaneously optimize economic objective (maximizing profit) and environmental objective (minimizing greenhouse gas emissions). The branch-and-refine algorithm is employed to accelerate the solution process. The proposed model then undergoes an illustrative case study scenario to verify its viable functionality. The result of the case study confirms that as more greenhouse gas emission is allowed, higher profit is generated.