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General-Purpose Modeling Environments for Discrete Optimization

用于离散优化的通用建模环境

基本信息

批准号：
9414487
负责人：
Robert Fourer
金额：
$ 24万
依托单位：
Northwestern University
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
1994
资助国家：
美国
起止时间：
1994-09-15 至 1998-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=9414487&HistoricalAwards=false
关键词：
General Purpose Modeling Environments Discrete

项目摘要

9414487 Fourer This research focuses on the identification and investigation of difficult conceptual issues that must be resolved in designing languages, interfaces, and algorithms for a broad classes of combinatorial optimization problems. The research aims to identify strategies for transferring discrete optimization technology to a broad range of users and to design general-purpose languages and environment that support application development in discrete optimization. The foundation of the research is provided by two system design elements, the algebraic modeling language and the algebraic toolkit, that have been used in the development of software in statistics and continuous optimization problems. This work will jointly consider the issue of representation and algorithms in developing the general-purpose software for combinatorial optimization. The research will have direct practical value to engineering education and the American industry. American industries engage daily in resolving problems that are combinatorial in nature. The outcome of this research will facilitate the ease of use of explicit models and powerful optimization technologies to resolve these problems. Industry will also benefit from the quality solution that can be obtained from the use of optimization models as against heuristic algorithms. From the engineering education view point, development of a general-purpose modeling software will play a key role in the teaching of large-scale optimization. This will allow student to formulate, solve, and analyze realistically large and complex models instead of dealing with textbook type problems that are generally small and contrived.

9414487 Fourer这项研究的重点是识别和调查在设计语言、接口和算法时必须解决的困难的概念问题，这些问题用于广泛的组合优化问题。该研究旨在确定将离散优化技术转移到广泛用户的策略，并设计支持离散优化应用开发的通用语言和环境。代数建模语言和代数工具箱这两个系统设计元素已经应用于统计和连续优化问题的软件开发，为本研究提供了基础。这项工作将共同考虑在开发通用组合优化软件中的表示和算法问题。该研究对工程教育和美国工业具有直接的实用价值。美国的工业每天都在解决本质上是组合性的问题。本研究的结果将有助于使用显式模型和强大的优化技术来解决这些问题。工业也将受益于通过使用优化模型而不是启发式算法获得的高质量解决方案。从工程教育的角度来看，开发通用的建模软件对大规模优化的教学具有重要意义。这将使学生能够制定、解决和分析实际的大型复杂模型，而不是处理通常小而人为的教科书式问题。