Mathematical models and algorithms to support the evolution of operational practices

支持操作实践演变的数学模型和算法

• 批准号: RGPIN-2021-03327
• 负责人: Gruson, Matthieu
• 金额: $ 1.89万
• 依托单位: Université du Québec à Montréal
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=755946
• 关键词: Mathematical; models; algorithms; support; evolution

Operations management is a field that witnessed numerous evolutions in the last decades. For instance, operations are now greener. The scientific community, and in particular the operations research (OR) experts, have successfully used their skills to model those evolutions and reach the objectives targeted by companies, whether in the manufacturing or service industry. For example, we now build vehicle routes that minimize the greenhouse gas emissions. Recently, several evolutions appeared in the operations management field: (i) the integration of operational decisions, (ii) Industry 4.0, and (iii) the focus on service development. The integration of operational decisions consists in making related decisions at once, such as the production and distribution decisions, instead of sequentially. This is known to bring numerous benefits, such as a decrease of operational costs and a better organizational performance, among others. Industry 4.0 is another kind of integration, between the virtual and physical worlds. This integration was made possible by the development of new technologies, among others, and facilitates the traceability of products, and a better use of resources, among others. Finally, the focus on service development consists here in combining operations research and revenue management to offer customers new possibilities. The long-term objective of my discovery research program is to develop mathematical models and algorithms, rooted in OR, to efficiently represent the evolution of operations practices coming from operational integration, Industry 4.0, and service development. In the short-term, we will focus on the implications of those evolutions in the areas of supply chain management, production planning and scheduling, and vehicle routing. First, we will model those new operations practices. Then, efficient solution algorithms will be designed to solve the resulting problems. Finally, we will analyze the impacts of the evolution of operations practices, and will propose innovative operational practices. The work done in this research program will be beneficial for both the scientific community and practitioners. From a scientific viewpoint, the developed algorithms will be able to solve large size instances, thus being consistent with the growing presence of massive data. We will also contribute to the new generation of classical OR problems. From a practical viewpoint, the research program will lead to the proposition of innovative operations practices. Those innovative practices will be validated after performing numerous numerical experiments and will contribute in return to the evolution of operations practices. Finally, this research program will be beneficial for students through the training of highly qualified personnel.

运营管理是一个在过去几十年中见证了许多演变的领域。例如，操作现在更绿。科学界，尤其是运营研究（OR）专家，已经成功地利用了他们的技能来建模这些发展，并达到公司针对的目标，无论是在制造业还是服务行业中。例如，我们现在建立了将温室气体排放量最小化的车辆路线。最近，运营管理领域中出现了几种演变：（i）运营决策的集成，（ii）行业4.0和（iii）关注服务开发。运营决策的集成在于一次做出相关决策，例如生产和分发决策，而不是顺序。众所周知，这会带来许多好处，例如运营成本的降低和更好的组织绩效。工业4.0是虚拟和物理世界之间的另一种整合。通过开发新技术，可以促进产品的可追溯性以及更好地利用资源等，从而使这种整合成为可能。最后，对服务开发的重点在于将运营研究和收入管理结合起来，为客户提供新的可能性。我的发现研究计划的长期目标是开发数学模型和算法，植根于OR，有效地表示来自运营集成，行业4.0和服务开发的操作实践的演变。在短期内，我们将重点关注这些演变在供应链管理，生产计划和计划以及车辆路线领域的影响。首先，我们将建模这些新的操作实践。然后，将设计有效的解决方案算法来解决产生的问题。最后，我们将分析运营实践进化的影响，并提出创新的运营实践。该研究计划中所做的工作将对科学界和从业者都有益。从科学的角度来看，开发的算法将能够解决大型实例，从而与大量数据的日益增长的存在一致。我们还将为新一代古典或问题做出贡献。从实际的角度来看，研究计划将导致创新操作实践的主张。这些创新的实践将在执行大量数值实验后得到验证，并将为操作实践的演变做出贡献。最后，通过培训高素质的人员，该研究计划将对学生有益。