Demand-driven optimization approach for biomass utilization networks

Building Biomass Networks (B-NETs) is one of the techniques used to overcome the seasonal fluctuation in biomass supply and tapping new utilizations ways. The B-NETs are built based on a super class model for the available and possible kinds of utilization processes in the local area. Hence, the decision of selecting possible networks and scenarios can be made before using optimization methods to fix on the optimal network. In this paper, an optimization model for a Demand-driven biomass processing network is proposed. This is done through selecting alternative production paths for the same product depending on the resources availability. The unit process capacities and biomass resource availability constraints were presented to overcome their limitations in the local area. The genetic algorithms (GAs) were used in solving the problem because of their ability to deal with large search spaces and capability to calculate material flows, through networks, with no previous estimations.

► The evaluation of biomass utilization networks using demand-driven optimization technique is addressed.
► A discussion about the importance of biomass utilization superstructure in local areas is given.
► A network model and a solution approach using Genetic Algorithms (GAs) are proposed.
► The GAs are used to estimate the material flows in the network with no need for previous estimates by the model user.