GDP-based approach for optimal design of forest biorefinery supply chain considering circularity and conversion facilities co-location

Abstract

The Forest Biorefinery Supply Chain (FBSC) design problem is addressed. A general mathematical framework based on a Generalized Disjunctive Programming (GDP) formulation is proposed as an efficient decision-making tool for the optimal FBSC. The approach simultaneously tackles the dynamic capacity allocation and the facilities’ co-location, features that are explicitly modelled. The FBSC superstructure promotes the circularity of the network by including flexible processing recipes and the use of multiple biomass residues as biorefineries raw materials as well as paper recycling. The proposed case study copes with the production of paper and biofuels in Argentina, showing the advantage of the integration of biorefineries with the existing forest industries as well as the addition of value to biomass industrial waste and by-products. Additionally, a set of scenarios are considered and tested. By these examples, key features of the proposed approach are highlighted as essential to reach a profitable FBSC.