Research in Mixed-Integer Programming

混合整数规划研究

• 批准号: 9115768
• 负责人: George Nemhauser
• 金额: $ 50万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1992
• 资助国家: 美国
• 起止时间: 1992-04-15 至 1997-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9115768&HistoricalAwards=false
• 关键词: Research; Mixed; Integer; Programming

The goal of this project is to develop algorithms and prototype software for solving large-scale mixed-integer programs and to develop application routines for solving problems that arise in distribution, manufacturing, production scheduling and resource allocation. The motivation behind this research is the tremendous demand for efficient and robust mixed-integer programming algorithms in the preceding domains. A Mixed-Integer Optimizer (Minto) system was developed by these researchers in prior projects. The MINTO system allows a researcher to customize general mixed- integer optimization code through application routines and concentrate on problem specifics rather that implementation details of tools like linear programming. The project will research methods to strengthen the capabilities of MINTO. It will also research the development of the application routines for generic problems in distribution, scheduling, manufacturing and resource allocation. Real application data will be used to test the customized systems.

这个项目的目标是开发算法和原型 软件解决大规模混合整数规划和 开发应用程序例程，用于解决 分销、制造、生产调度和资源 配置中 这项研究背后的动机是巨大的 对高效和鲁棒混合整数规划的需求 在前面的领域的算法。 一种混合优化算法 （Minto）系统是由这些研究人员在以前开发的。 项目 MINTO系统允许研究人员定制一般的混合- 通过应用程序例程进行整数优化代码， 专注于问题的细节，而不是实现的细节， 线性规划之类的工具。 该项目将研究加强能力的方法 关于MINTO 并对应用的发展进行研究 在分配，调度， 生产和资源配置。 真实的应用程序数据将 用于测试定制的系统。