Cost-efficient optimization of forest biorefinery supply chain for energy and chemicals production considering forestry planning decisions

PIEDRA-JIMENEZ, F; TASSIN, N; NOVAS, JM; BROZ, D; RODRÍGUEZ, MA

Cambridge, MA

Conferencia; 2022 MIT SCALE Conference for Latin America and the Caribbean; 2022

The aim of present work is to propose a general mathematical framework based on a Generalized Disjunctive Programming (GDP) approach for the optimal design of Forest Biorefinery Supply Chain (FBSC) integrating forest planning decisions. For this purpose, a GDP model is constructed which it is reformulated as a Mixed Integer Linear Model (MILP). The model determines: the location, size, technology and capacity profile of the facilities throughout the FSC; as well as the land area to be harvested for each tree species considered and the biomass flows in each of the links of the chain. In order to validate the proposal, a representative case study of the national forest industry is tackled, considering the co-location of bioenergy and biorefinery facilities with traditional forest industries.