CAREER: A Study of Stochastic and Robust Integer Programming: Algorithms, Computations and Applications

职业：随机和鲁棒整数规划研究：算法、计算和应用

• 批准号: 0942156
• 负责人: Yongpei Guan
• 金额: $ 40万
• 依托单位: University of Florida
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-05-17 至 2014-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0942156&HistoricalAwards=false
• 关键词: CAREER; Study; Stochastic; Robust; Integer

This Faculty Early Career Development (CAREER) award provides funds for research and education activities to advance the theory, computations and applications of stochastic and robust integer programming. Integer decision variables are commonly used in models for decision making problems. Moreover, in real-time decision making problems, instance parameters are usually uncertain. This work will study stochastic and robust integer programming approaches to formulate and solve decision making problems with integer decision variables and uncertain parameters. The research activities include 1) studying polyhedral structures and polynomial time algorithms for fundamental problem formulations, 2) discovering new methods to integrate cutting planes with decomposition algorithms, 3) exploring cyberinfrastructure to implement the algorithms efficiently in high performance computing facilities, and 4) integrating theoretical analysis with application problems in power asset optimization, joint pricing and inventory planning, and weather forecasting and evacuation plans. The education activities include 1) promoting the practice of stochastic and robust integer programming as an efficient approach to solve decision making under uncertainty problems and 2) stimulating student interest in research in science and technology, especially in operations research. The research and education tasks are integrated in a way that both benefit from each other. If successful, the results of the research activities will lead to methodology innovations for solving large-scale decision making under uncertainty problems and advance the utilization of cyberinfrastructure in optimization. These research outcomes will provide new methodologies that can be used to instruct the next generation of engineers on efficient optimization methods. In addition, the activities will have big impact on industry and society by disseminating advanced methodologies to practitioners and providing outreach to underrepresented minority students, through collaborations with local industry and research centers such as Center for Engineering Logistics and Distribution, Center for Analysis and Prediction of Storms, and the K20 Center.

这项教师早期职业发展（职业）奖为研究和教育活动提供了资金，以推动随机和健壮的整数编程的理论，计算和应用。整数决策变量通常用于决策问题的模型中。此外，在实时决策问题中，实例参数通常不确定。这项工作将研究随机且强大的整数编程方法，以用整数决策变量和不确定参数来制定和解决决策问题。研究活动包括1）研究基本问题配方的多面体结构和多项式时间算法，2）发现将切割平面与分解算法集成的新方法，3）探索Cyber​​infrasture，以在高性能计算设施中有效地实施算法，以及4）4）理论分析与电力资产优化，联合定价和库存计划以及天气预报和疏散计划中的应用问题有关。教育活动包括1）促进随机且强大的整数编程的实践，作为在不确定性问题下解决决策的有效方法； 2）刺激学生对科学和技术研究的兴趣，尤其是在运营研究中。研究和教育任务以彼此受益的方式整合。如果成功，研究活动的结果将导致方法论在不确定性问题下解决大规模决策并提高网络基础设施在优化中的利用。这些研究结果将提供新的方法，可用于指导下一代工程师有效的优化方法。此外，通过与当地行业和研究中心（例如工程物流中心和分销中心，分析和预测中心）的合作，通过向从业者传播先进的方法，并向代表性不足的少数群体学生提供宣传，并为行业和社会产生重大影响。风暴和K20中心。