Value Chain Network Design and Planning Under Uncertainty for a Sustainable and Resilient Forest industry

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The Canadian forest industry seeks to transform its economy through novel bioproducts and new technologies to diversify its products portfolio and entering into new markets with high end-value products. This transformation adds additional risks due to the uncertainty of the new markets (demand and price), new advanced materials, associated technologies, new supply, and integration with existing value chains (competition). Uncertainty is also a major feature in forestry management since it deals with uncertain biological and natural processes, large forest territories and decisions over long-term planning horizon. Stakeholders (Governments, industry and communities) have conflicting objectives and facing difficult decisions such as: Which investment should be made? Which companies should be allocated timber license (species, volume, etc.)? What is the impact on local communities as well as the environment? On the other hand, they agree to manage the forest resources in a sustainable way to simultaneously reduce the environmental and social impact and increase the economic impact. Decision supports systems (DSSs) based on operations research has been introduced to manage value chain in the forest sector and now are used by governments and industry. Most of (if not all) are based on deterministic models or sometimes are combined with some hedging against shortage strategies (safety stock to protect against demand uncertainty). The most commonly used methodologies in forest planning are sensitivity analysis and scenario based analysis. The most deficiency of these two methods is their inability to evaluate the impact of interactions between the various stochastic parameters and a lack of knowledge concerning the probability of occurrence of each scenario. These drawback limits the usage and reduces the trust of decision makers on these DSSs and thus the ability to apply the decisions provided by the DSSs. **There is a lack of approaches and tools which include uncertainty and risk modeling that can be used to answer the challenging questions to support the stakeholders in the transition of the forest industry to more competitive and sustainable over time. Stochastic programming (SP) and robust optimization (RO) have not been used to deal with uncertainty and risk due to many reasons such as they involve very large models with long solution times, require information about uncertainty and distributions and finally lack of knowledge and expertise to deal with this types of modeling and optimization. In this proposal, we aim to develop advanced approaches to design and plan robust network for the forest biorefinery value chains taking into account uncertainty through mathematical programming techniques, approaches to model uncertainty and efficient methods and algorithms to solve such complex problems. By forest biorefinery, we mean full integration of the incoming biomass and other raw materials, including energy, for simultaneous production of fibers for paper products, chemicals, energy, and lumber products. Supply chain design and planning is a key element of the success of this industry shift and should be studied to ensure sustainable and resilient forest industry. Design and planning of the supply chain network is complex and deals with strategic and tactical decisions such as forest management strategies, technology investments, resource allocation of forests to mills, etc. *This program will lead to new solutions robust and stable solutions with less need of re-planning, assist the various stakeholders address the design and planning of value chains that are economically, environmentally and socially sustainable while considering many different various sources of uncertainty.