Decision making in the forest value chain

该提案的主要目标是开发决策支持工具，通过分析提高未来加拿大森林生物经济价值链的竞争力。分析使组织能够将复杂的挑战转化为实质性的机遇，将数据转化为信息，并将信息转化为洞察力，以更好地制定决策和改进结果。另一个关键目标是利用大数据结合分析技术和工具来减少污染，从而刺激森林社区的生存能力，并使物流和运输业务更加高效。该建议是FORAC 4.0研究计划的一部分，并从过去15年来研究联盟进行的成功研究工作中延伸出来。工业界领袖和学术界人士都已经确定了解决的问题。在我们这边，我们组建了一个由来自工业工程、商业分析、森林工程和计算机科学领域的研究人员和学生组成的多学科团队。通过这样做，我们确定了研究和技术转让成功的一个关键因素：与工业伙伴的密切合作。这些合作伙伴将为案例研究提供问题见解、数据、设施、结果分析，并成为技术转让的接受者。13个多学科和团队培训的HQP将是一个重要的成果，在这个建议（4博士，5名硕士，4实习）。

The primary objective of this proposal is to develop decision support tools, enhancing the competitiveness offuture Canadian forest bioeconomy value chains through analytics. Analytics enable organizations to turncomplex challenges into substantial opportunities by transforming data into information and information intoinsight for better decision-making and result improvement. Another key objective is to leverage Big Data inconjunction with analytics techniques and tools to reduce pollution, thereby stimulating the viability offorest-based communities and making logistics and transportation operations more efficient. This proposal ispart of the FORAC 4.0 research program and extends from successful research efforts conducted by theresearch consortium over the last 15 years. Both industrial leaders and academics have identified the problemsaddressed. On our end, we assembled a multidisciplinary team of researchers and students from the industrialengineering, business analytics, forest engineering, and computer science fields. In so doing, we identified akey factor for success in research and technology transfer: a close collaboration with industrial partners. Thesepartners will provide problem insight, data, facilities, result analysis for case studies, and be receivers oftechnology transfer. Thirteen multidisciplinary and team-trained HQP will be an important outcome duringthis proposal (4 Ph.D., 5 M.Sc., and 4 internships).