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

不确定性下的价值链网络设计和规划，实现可持续和有弹性的林业

• 批准号: RGPIN-2014-05705
• 负责人: Ouhimmou, Mustapha
• 金额: $ 1.75万
• 依托单位: École de technologie supérieure
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=636823
• 关键词: Value; Chain; Network; Design; Planning

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.

加拿大森林业寻求通过创新的生物产品和新技术实现经济转型，使其产品组合多样化，并以高端产品进入新市场。由于新市场(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整合(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大特点，因为它涉及不确定的生物和自然过程、大片森林领地和长期规划范围内的决策。利益相关者(政府、行业和社区)的目标相互冲突，面临着艰难的决定，例如：应该进行哪种投资？哪些公司应该获得木材许可证(品种、材积等)？这对当地社区和环境有什么影响？另一方面，双方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，增加经济影响。建立在运筹学基础上的决策支持系统(DSS)已被用于管理林业部门的价值链，目前正在被政府和工业界使用。大多数(如果不是全部的话)都是基于确定性模型，或者有时与一些针对短缺策略的对冲策略(安全库存，以防止需求不确定性)相结合。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。这两种方法最大的缺点是不能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景发生概率的知识。这些缺陷限制了对这些DSS的使用并降低了决策者对这些DSS的信任，从而降低了应用DSS提供的决策的能力。缺乏方法和工具，包括可用于回答挑战性问题的不确定性和风险建模，以支持利益攸关方逐步向更具竞争力和可持续的森林工业过渡。随机规划(SP)和稳健优化(RO)一直没有被用来处理不确定性和风险，原因有很多，例如它们涉及非常大的模型，求解时间长，需要关于不确定性和分布的信息，最后缺乏处理这种类型的建模和优化的知识和专业知识。在这项提案中，我们的目标是通过数学规划技术、不确定性建模方法以及解决此类复杂问题的有效方法和算法，开发先进的方法来设计和规划考虑不确定性的森林生物精炼价值链的健壮网络。我们所说的森林生物炼油厂，是指将输入的生物质和其他原材料(包括能源)完全整合在一起，同时生产用于纸制品、化学品、能源和木材产品的纤维。供应链的设计和规划是这一产业转移成功的关键要素，应加以研究，以确保林业的可持续性和复原力。供应链网络的设计和规划是复杂的，涉及战略和战术决策，如森林管理战略、技术投资、森林资源分配给磨坊等。该计划将产生新的解决方案，强大和稳定的解决方案，减少重新规划的需要，帮助不同的利益相关者解决在经济、环境和社会上可持续的价值链的设计和规划，同时考虑许多不同的各种不确定性来源。