Global optimization for nonlinear supply chain management under uncertainty

不确定性下非线性供应链管理的全局优化

• 批准号: 485798-2015
• 负责人: Li, Xiang
• 金额: $ 1.09万
• 依托单位: Queen's University
• 依托单位国家: 加拿大
• 项目类别: Collaborative Research and Development Grants
• 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=618266
• 关键词: Global; optimization; nonlinear; supply; chain

Supply chain optimization (SCO) is the optimal coordination of production, inventory, location, and transportation in the supply chain to achieve one or multiple goals for the whole system. The efficiency and quality of SCO decision-making procedure is crucial to the sustainability of a company, financially, economically, and socially. However, the sustainability considerations and the unavoidable uncertainties make SCO problems very difficult mathematical optimization problems that can not be well solved using classical formulation and solution approaches. This research is to utilize the recent advances in global optimization of uncertain nonlinear process systems, to develop more efficient and reliable solution strategies for SCO under uncertainty. It involves two projects. The first project is to enhance an existing decomposition-based global optimization method for strategic SCO problems that are mainly concerned with supply chain network design. The second project is to develop new formulations and global optimization methods for integrated strategic and tactical SCO problems, which optimize supply chain design and operational decisions simultaneously. The research will be conducted in collaboration with DuPont Canada. The results of the research cannot only benefit DuPont, but also other companies that want to achieve sustainable supply chain development and operation. The software packages developed in the research can be potentially commercialized, leading to new spin-off companies and more jobs for Canadians. One master's student and one Ph.D. student will be trained through the proposed research, and they will acquire knowledge and skills widely sought by Canada's industries.

供应链优化（SCO）是供应链中生产，库存，位置和运输的最佳协调，以实现整个系统的一个或多个目标。 SCO决策程序的效率和质量对于公司在经济，经济和社会上的可持续性至关重要。但是，可持续性考虑和不可避免的不确定性使SCO问题非常困难的数学优化问题，这些问题无法通过经典的配方和解决方案方法得到很好的解决。这项研究是利用不确定非线性过程系统的全球优化的最新进展，以在不确定性下为SCO制定更有效和可靠的解决方案策略。它涉及两个项目。第一个项目是为主要与供应链网络设计有关的战略SCO问题增强现有的基于分解的全球优化方法。第二个项目是为综合战略和战术SCO问题开发新的配方和全球优化方法，该方法同时优化了供应链设计和操作决策。该研究将与加拿大杜邦合作进行。研究结果不仅使杜邦受益，而且还使其他想要实现可持续供应链开发和运营的公司。研究中开发的软件包可能会成为可能商业化，从而为加拿大人提供了新的衍生公司和更多的就业机会。一个硕士的学生和一位博士学位。学生将通过拟议的研究对学生进行培训，他们将获得加拿大行业广泛寻求的知识和技能。