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

加拿大森林工业寻求通过新的生物产品和新技术来改变其经济，使其产品组合多样化，并进入具有高最终价值产品的新市场。由于新的市场（需求和价格）、新的先进材料、相关技术、新的供应以及与现有价值链的集成（竞争）的不确定性，这种转变增加了额外的风险。不确定性也是林业管理的一个主要特点，因为它涉及不确定的生物和自然过程、大片森林领土和长期规划范围内的决定。利益相关者（政府、行业和社区）的目标相互冲突，并面临困难的决定，例如：应该进行哪些投资？哪些公司应该获得木材许可证（种类、数量等）？对当地社区和环境的影响是什么？另一方面，他们同意以可持续的方式管理森林资源，同时减少对环境和社会的影响，增加对经济的影响。基于运筹学的决策支持系统（DSSs）已被引入森林部门的价值链管理，目前已被政府和行业使用。大多数（如果不是全部）都是基于确定性模型，或者有时结合一些针对短缺的对冲策略（安全库存以防止需求不确定性）。森林规划中最常用的方法是敏感性分析和基于情景的分析。这两种方法的最大缺陷是它们无法评估各种随机参数之间相互作用的影响，并且缺乏关于每种情况发生概率的知识。这些缺点限制了使用，并降低了决策者对这些决策支持系统的信任，从而降低了应用决策支持系统提供的决策的能力。

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.