A mathematical model for cost optimization of bioethanol production integrated into pulp and paper supply chain: The impact of scale and capacity strategies

Abstract

A mathematical model for the pulp and paper supply chain (P&PSC) network design is presented in this work, where the integration of bioethanol production is evaluated. The optimization model is used to analyze the impact of three cost reduction strategies: economies of scale, transport, and dynamic capacity. The problem is formulated as a generalized disjunctive programming (GDP) model and reformulated as mixed integer linear programming (MILP) one. It is implemented in GAMS and its feasibility has been tested using data from a real case study from Argentina.