Forest biomass is one of the renewable and sustainable sources of energy that can be used for producing electricity, heat, and biofuels. The complex supply chain of forest biomass for energy generation, which consists of different players and products and is affected by biomass characteristics, such as low density and unpredictable quality, makes the energy generation cost from biomass higher than that of the conventional sources of energy, such as fossil fuels. Moreover, variability and uncertainty in this supply chain, mainly due to the nature of material, economic condition and market fluctuation, affect the amount of produced energy and its cost. Mathematical modeling, in particular optimization techniques, can be employed to manage the supply chain and achieve the optimum design. This paper reviews studies which used deterministic and stochastic mathematical models to optimize forest biomass supply chains for electricity, heat and biofuels production. Optimization models were used to provide the optimum solution for decisions related to the network design, technology choice, plant size and location, storage location, mix of products and raw materials, logistics options, supply areas, and material flows. Mainly, economic objectives were considered in these models. Further studies should consider environmental and social objectives, in addition to the economic ones, in the models. In non-deterministic models uncertainty mainly in the demand, supply, prices, and conversion yields were incorporated. Although material quality is an important uncertain parameter in the forest biomass supply chain that affects the amount and cost of produced energy, its variation was not considered in previous studies.
