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Data-Driven Approaches for Large-Scale Optimization

Data-Driven Approaches for Large-Scale Optimization
用于大规模优化的数据驱动方法
批准号:
RGPIN-2017-03999
负责人:
Elhedhli, Samir
金额:
$2.04万
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:
2017
资助国家:
加拿大
项目状态:
已结题
起止时间:
2017-01-01 至 2018-12-31

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中文摘要
翻译
面对十多年来收集的大量数据,来自运输和电信等各个行业的公司都在寻求将这些数据转化为信息,以创造竞争优势。最重要的是,他们希望使用它来评估、优化和验证他们的操作、流程和业务模型。随着数据的可用性和计算能力的提高,有机会构建直接使用数据的优化模型。
英文摘要
Faced with massive amounts of data that has been collected for over a decade, companies from a variety of industries, such as transportation and telecommunication, are looking to transform this data to information in order to create competitive advantage. Most importantly, they are hoping to use it to assess, optimize, and validate their operations, processes, and business models. With data availability and the improvements in computational power, there is an opportunity to build optimization models that make direct use of the data.
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Data-driven logistics and distribution planning: Emerging trends and pandemic-related challenges
  • 批准号:
    RGPIN-2022-03530
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.62万
  • 财政年份:
    2022
  • 负责人:
    Elhedhli, Samir
  • 依托单位:
Data-Driven Approaches for Large-Scale Optimization
  • 批准号:
    RGPIN-2017-03999
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.04万
  • 财政年份:
    2021
  • 负责人:
    Elhedhli, Samir
  • 依托单位:
Data-Driven Approaches for Large-Scale Optimization
  • 批准号:
    RGPIN-2017-03999
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.04万
  • 财政年份:
    2020
  • 负责人:
    Elhedhli, Samir
  • 依托单位:
Data-Driven Approaches for Large-Scale Optimization
  • 批准号:
    RGPIN-2017-03999
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.04万
  • 财政年份:
    2019
  • 负责人:
    Elhedhli, Samir
  • 依托单位:
国内基金
海外基金
Data-driven Recommendation System Construction of an Online Medical Platform Based on the Fusion of Information