Faculty Early Career Development: Industry-University Partnership in Logistics -- Dynamic Thinking in Research and Education

9501446 这项研究的重点是建立一个行业和大学的合作伙伴关系，以支持新的算法和方法的发展，在物流实时决策的问题。 在一个典型的物流系统中，经常需要在车辆路线、船舶调度、车辆库存管理和使用不断变化的信息设计服务产品方面进行实时决策。 卫星与高速数据网络相结合等新技术使决策者能够获得实时数据。 这些新技术推动了新的随机动态模型的发展，以实现更准确的决策。 本研究提出了一套模型的问题，从实时车辆路径的动态服务网络设计。 一个共同的数学基础，重点是随机优化和动态网络建模。 新的决策模型将根据需求水平、旅行时间、服务故障和资源可用性的各种随机性来源进行开发。 将继续使用图形可视化来验证模型并将结果传达给模型用户。 建立产业与大学的伙伴关系不仅是为了支持研究，并就将要开发的模型的相关性提出建议，而且也是为了影响物流教育课程。 要在研究和教育方面建立强有力的产学合作伙伴关系，就需要在改革课程方面做出巨大努力。 这项工作教育部分的目标是： (1)提高行业对大学教育的参与，（2）为行业合作伙伴开发新的培训计划，（3）开发计算物流实验室，（4）为物流行业的学生增加实习和合作机会，以及（5）提高学生在物流领域建模和解决问题的技能。 这项研究对学生和产业工人的影响将是巨大的。 本研究具有直接的工业应用价值，如果成功，将提高物流和分销行业的经济竞争力。

9501446 This research is focused on the issue of building an industry-university partnership to support the development of new algorithms and methods for real-time decision making in logistics. In a typical logistics system, there is a regular need for real-time decision making in vehicle routing, scheduling of vessels, management of vehicle inventories, and design of service offerings using constantly changing information. New technologies such as the combination of satellites with high-speed data networks are making real-time data available to decision makers. These new technologies have motivated the development of new stochastic, dynamic models for more accurate decision making. This research presents a set of models for problems ranging from real-time vehicle routing to dynamic service network design. A common mathematical foundation is presented that focuses on stochastic optimization and dynamic network modeling. New decision models will be developed subject to various sources of randomness in demand level, travel times, service breakdowns, and resource availability. The use of graphical visualization for validating models and communicating results to model users will be pursued. The establishment of an industry-university partnership is not only to support the research and advise on the relevancy of the models to be developed but also to influence the educational curriculum in logistics. Establishing a strong industry-university partnership in research and education requires a substantial effort in reforming the curriculum. The goals of the educational component of this work are: (1) to increase industry participation in university education, (2) develop new training programs for industry partners, (3) develop a laboratory for computational logistics, (4) increase internship and co-op opportunities for students in the logistics industry, and (5) improve the technical skills of students in modeling and solving problems in the field of logistics. The impact of the resear ch to stu dents and industrial workers will be significant. The research has direct industrial application and if successful, will improve the economic competitiveness of the logistics and distribution industries.