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EAGER: Optimization without Round-off Errors

EAGER: Optimization without Round-off Errors
EAGER:无舍入误差的优化
批准号:
1252456
负责人:
Erick Moreno-Centeno
金额:
$12.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2012
资助国家:
美国
项目状态:
已结题
起止时间:
2012-09-15 至 2016-08-31

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中文摘要
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英文摘要
This Early-concept Grant for Exploratory Research (EAGER) provides funding to further develop an algorithm to solve systems of linear equations with a specific advantage over Gaussian Elimination in that the algorithm does not have round-off errors. The algorithm will be tailored and adapted to be used within existing optimization algorithms. The key property of the algorithm being further developed is that it maintains the integrality of the numbers throughout its execution. In particular, although the algorithm does contain divisions (which is crucial for the polynomial-time complexity of thealgorithm) all the divisions have a remainder of zero. A detailed complexity analysis of the algorithm will be performed; specifically, both its running time and the number of bits required to represent the numbers throughout the algorithm's execution will be investigated. A modification of the algorithm to perform LU factorizations will also be studied. Finally, the algorithm will be adapted to enable its use for the basis updates performed in state-of-the-art implementations of the revised simplex method.If successful, the outcomes of this research will lead to a deeper understanding of computational linear algebra free of round-off errors and the associated applications within optimization algorithms. In the linear programming (LP) context, this research will enable us to solve large-scale LPs exactly; this, in turn, will significantly improve the accuracy and speed of integer programming solvers. In addition, since solving systems of linear equations is a critical subroutine of many numerical algorithms, this research will impact many application areas where linear systems frequently arise, including economics, physics, chemistry, and engineering.
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会议论文
Elements: Software: Roundoff-Error-Free Algorithms for Large-Scale, Sparse Systems of Linear Equations and Optimization
EAGER: Topology Control for Enhancing the Reliability of the National Power Grid
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
供应链管理中的稳健型(Robust)策略分析和稳健型优化(Robust Optimization )方法研究
  • 批准号:
    70601028
  • 项目类别:
    青年科学基金项目
  • 资助金额:
    7.0万元
  • 批准年份:
    2006
  • 负责人:
    王明征
  • 依托单位: