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Rigorous Search Space Reduction

Objective

In our world of big data and theoretically intractable problems, automated preprocessing to simplify problem formulations before solving them algorithmically is growing ever more important. Suitable preprocessing has the potential to reduce computation times from days to seconds. In the last 15 years, a framework for rigorously studying the power and limitations of efficient preprocessing has been developed. The resulting theory of kernelization is full of deep theorems, but it has overshot its goal: it does not explain the empirical success of preprocessing algorithms, and most questions it poses do not lead to the identification of preprocessing techniques that are useful in practice. This crucial flaw stems from the fact that the theoretical kernelization framework does not address the main experimentally observed cause of algorithmic speed-ups: a reduction in the search space of the subsequently applied problem-solving algorithm.

REDUCESEARCH will re-shape the theory of effective preprocessing with a focus on search-space reduction. The goal is to develop a toolkit of algorithmic preprocessing techniques that reduce the search space, along with rigorous mathematical guarantees on the amount of search-space reduction that is achieved in terms of quantifiable properties of the input. The three main algorithmic strategies are: (1) reducing the size of the solution that the solver has to find, by already identifying parts of the solution during the preprocessing phase; (2) splitting the search space into parts with limited interaction, which can be solved independently; and (3) identifying redundant constraints and variables in a problem formulation, which can be eliminated without changing the answer.

This will raise the scientific study of preprocessing to the next level. Since physical limits form a barrier to further speeding up computer hardware, future advances in computing power rely on algorithmic breakthroughs as envisioned here.

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Keywords

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Programme(s)

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Topic(s)

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Funding Scheme

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ERC-STG - Starting Grant

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Call for proposal

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(opens in new window) ERC-2018-STG

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Host institution

TECHNISCHE UNIVERSITEIT EINDHOVEN
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 1 473 020,00
Address
GROENE LOPER 3
5612 AE Eindhoven
Netherlands

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Region
Zuid-Nederland Noord-Brabant Zuidoost-Noord-Brabant
Activity type
Higher or Secondary Education Establishments
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 1 473 020,00

Beneficiaries (1)

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