Multi-objective optimization design of sustainable biofuel network with integrated fuzzy analytic hierarchy process

Biofuel is one of the emerging sources of renewable energy, which is produced from biomass materials called feedstocks. Wood biomass, in particular, can improve air quality by reducing the smoke created by burning woody biomass. In this research, our key objective is to model the wood biomass supply chain to promote the effective operation of biofuel. Initially, we propose the mixed integer linear programming (MILP) model with multiple objectives for assessing the biofuel supply chain. Next, the fuzzy analytic hierarchy process (FAHP) is applied to assess uncertain data from decision makers and integrated with the proposed mathematical model. The developed model evaluates the perspective of sustainability by considering total cost - the surrogate criterion for the economic aspect, unsatisfied demand - the surrogate criterion for the social aspect, and CO2 emission - the surrogate criterion for the environmental aspect, into account. Next, both the supply of wood biomass from each farm node and the demand for produced electricity are evaluated with probabilistic scenarios and stochastic analysis in our analysis. Then, the sensitivity analysis and Pareto analysis are performed by varying parameters related to objective weights to verify and validate the model functionalities and objective tradeoffs. Finally, the regional case study in Thailand based on the wood-biomass data is applied with a realworld context to validate the model functionalities. Given that farmers' locations in the case study are distant with diverse areas, the results of tradeoff analysis in our study can provide a strategic choice for enhancing competitive advantages for key decision makers in the biofuel network.