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New Efficient Methods for Challenging Computational Optimization Problems

New Efficient Methods for Challenging Computational Optimization Problems
解决计算优化问题的有效新方法
批准号:
327684-2012
负责人:
Coleman, Thomas
金额:
$1.82万
依托单位:
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2012
资助国家:
加拿大
项目状态:
已结题
起止时间:
2012-01-01 至 2013-12-31

项目摘要

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中文摘要
翻译
在许多应用领域,人们对高效和实用的计算优化方法的兴趣和需求与日俱增。我们提出的研究将为计算优化中的三个这样的问题发展方法论、理论基础和理解。所有这三个问题都是困难的,需要计算,但开发有效解决方案的进展不仅将在优化领域产生广泛影响,而且将在科学计算和更广泛的应用中产生广泛影响。
英文摘要
There is a growing interest in, and demand for, efficient and practical computational optimization methods in numerous application domains. Our proposed research will develop methodology, and theoretical underpinnings and understanding, for three such problems in computational optimization. All three problems are hard, and computationally demanding, but progress on developing effective solutions will have broad impact not only in the field of optimization but across scientific computing and applications more generally.
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Large-scale Application of Automatic Differentiation in Computational Finance (and beyond)
  • 批准号:
    RGPIN-2017-03860
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.48万
  • 财政年份:
    2020
  • 负责人:
    Coleman, Thomas
  • 依托单位:
Large-scale Application of Automatic Differentiation in Computational Finance (and beyond)
  • 批准号:
    RGPIN-2017-03860
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.48万
  • 财政年份:
    2019
  • 负责人:
    Coleman, Thomas
  • 依托单位:
Large-scale Application of Automatic Differentiation in Computational Finance (and beyond)
  • 批准号:
    RGPIN-2017-03860
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.48万
  • 财政年份:
    2018
  • 负责人:
    Coleman, Thomas
  • 依托单位:
Large-scale Application of Automatic Differentiation in Computational Finance (and beyond)
  • 批准号:
    RGPIN-2017-03860
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.48万
  • 财政年份:
    2017
  • 负责人:
    Coleman, Thomas
  • 依托单位:
海外基金