A bi-objective robust model for minimization of costs and emissions of syngas supply chain

•Developed a bi-objective model to minimize cost and emission of syngas supply chain.•Syngas from gasification of forest biomass would be used in the lime kiln of a pulp mill.•Uncertainties in cost and supply of biomass were modelled via robust optimization.•Uncertainty led to solutions with 68% higher cost and 41% higher emissions on average.•Unlike deterministic, robust solutions had worse objectives but no infeasibility. Producing syngas from forest-based biomass could facilitate the transitions in energy and forest sectors by replacing natural gas; reducing emissions and wastes; and generating revenues. Optimizing the economic and environmental impacts of the biomass supply chains can help realizing these benefits. In this study, a bi-objective robust optimization model is developed for tactical supply chain planning of forest biomass gasification at a pulp mill. It optimizes the monthly flow, inventory, and preprocessing of biomass while minimizing annual costs and emissions. Robust optimization with an adjustable risk of constraint violation is used to model the uncertainties in supply and cost of biomass. The average cost and emissions of the robust Pareto-optimal solutions are 68% and 41% higher than those in the deterministic solutions, respectively. Although, the cost and emissions and their trade-off in the deterministic case are more favorable, the robust solutions ensure no biomass shortage while avoiding over-conservatism.