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Local reoptimization for turbocharging heuristics

Local reoptimization for turbocharging heuristics
涡轮增压启发式的局部重新优化
批准号:
DP150101134
负责人:
Prof Joachim Gudmundsson
金额:
$24.5万
依托单位:
依托单位国家:
澳大利亚
项目类别:
Discovery Projects
财政年份:
2015
资助国家:
澳大利亚
项目状态:
已结题
起止时间:
2015-06-01 至 2019-05-31

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中文摘要
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英文摘要
Theoretical computer science has up until now had little impact on the design of effective heuristics. While data sets may be large, significant structure is almost always present and important to take into account when designing algorithms. Parameterised complexity considers the underlying structure by parameterising not only on the size of the input but also on structural parameters. This project aims to take advantage of the many opportunities for new theories in the design of new heuristics and in turbocharging existing heuristics for computationally hard problems.
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Algorithms for Future-Proof Networks
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  • 项目类别:
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  • 资助金额:
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  • 财政年份:
    2024
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Devising tools for big data sets to support computational movement analysis
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  • 项目类别:
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  • 负责人:
    Prof Joachim Gudmundsson
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Algorithms and data structures to support automated analysis of trajectory data
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    FT100100755
  • 项目类别:
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    2011
  • 负责人:
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  • 依托单位:
海外基金