Interfacing Optimization and Applications

接口优化及应用

• 批准号: 9972372
• 负责人: Michael Ferris
• 金额: $ 26.67万
• 依托单位: University of Wisconsin-Madison
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1999
• 资助国家: 美国
• 起止时间: 1999-09-01 至 2003-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9972372&HistoricalAwards=false
• 关键词: Interfacing; Optimization; Applications

Modeling languages are heavily used in practice and therefore supply a critical vehicle for collaborative research in optimization. This project will faciliate this interaction by broadening the usage of optimization tools and environments in application areas. Due to the increasing demands in the size and complexity of applications, it has become vitally important for mathematical programmers to develop algorithms and tools within a modeling framework in order to advance the state-of-the-art in both applications and optimization. The thrust of the research will be in providing explicit examples of optimization technology, within targeted projects, and will address computational and tlieoretical aspects of large scale optimization in a practical setting.The new tools, environments, and algorithms of this proposal will enable an interactive approach to modeling with direct input from application and optimization experts during model development. The proposal will demonstrate such interactions within four application areas, namely the architectural design of video on-demand systems, cancer treatment plans in the context of tomotherapy, mathematical programming approaches to data mining, and the solution of complementarity problems arising in economics. A pivotal need is for visualization of optimization results within the application; a link between modeling languages and MATLAB will be provided for this purpose. An additional benefit of this link is the provision of a sophisticated mathematical programming capability to the MATLAB programniing environment.To address important issues and facets identified by domain experts, the resulting optimization problems are very large and require vast amounts of computing resources. Several new tools to enable the formulation and solution of such optimization problems on a metacomputer will be generated, all utilizing a pool of pre-existing, "off-the-shelf" workstations via Condor. A key component of the research will derive new algorithms that work within the proposed framework and exploit the metacomptiting resources. These include several new solvers for large scale complementarity problems and a fault tolerant parallel mixed integer programming solver.A fundamental goal of this effort is to educate researchers in other disciplines, primarily senior level undergraduates and graduate students, on the utility, use and power of these tools. Several of the application collaborations detailed in this proposal are direct consequences of interactions with colleagues and students during the first teaching of a course based on the topics of this project.

建模语言在实践中被大量使用，因此为优化中的协作研究提供了关键工具。 该项目将通过在应用领域扩大优化工具和环境的使用来促进这种互动。 由于对应用程序的规模和复杂性的需求不断增加，数学程序员在建模框架内开发算法和工具以推进应用程序和优化的最新技术变得至关重要。 该研究的重点将是在目标项目中提供明确的优化技术示例，并将在实际环境中解决大规模优化的计算和理论问题。该提案的新工具、环境和算法将在模型开发过程中通过应用和优化专家的直接输入实现交互式建模方法。 该提案将展示四个应用领域内的这种相互作用，即视频点播系统的架构设计，癌症治疗计划的背景下，断层治疗，数学编程方法的数据挖掘，以及解决经济学中出现的互补性问题。 一个关键的需求是在应用程序中的优化结果的可视化;建模语言和MATLAB之间的链接将为此目的提供。 这个链接的另一个好处是为MATLAB编程环境提供了复杂的数学编程能力。为了解决领域专家确定的重要问题和方面，由此产生的优化问题非常大，需要大量的计算资源。 几个新的工具，使制定和解决这些优化问题的元计算机将产生，所有利用池预先存在的，“现成的”工作站通过秃鹰。 研究的一个关键组成部分将得出新的算法，工作在拟议的框架和利用元计算资源。 其中包括几个新的解决大规模互补问题和容错并行混合整数规划solvers.A的一个基本目标，这项工作是教育研究人员在其他学科，主要是高年级本科生和研究生，对这些工具的效用，使用和权力。 本提案中详细介绍的几个应用程序合作是基于本项目主题的课程第一次教学期间与同事和学生互动的直接结果。