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A Fast Randomized Algorithm for Multi-Objective Query Optimization

Summary: First polynomial-time, randomized algorithm for multi-objective query optimization. Iterative, multi-objective hill climbing with multiple transformations and a Pareto-cache of intermediate results enables scalable search over join orders and outperforms NSGA-II on large queries. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5180
Venue
SIGMOD
Year
2016
Pagerank
5.3607984e-05
Overall Rank
8,831 | 39.42%
DOI
10.1145/2882903.2882927

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{trummer_sigmod16,
        title = {{A Fast Randomized Algorithm for Multi-Objective Query Optimization}},
        author = {Trummer, Immanuel and Koch, Christoph},
        series = {{SIGMOD} '16},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/2882903.2882927},
        url = {https://dl.acm.org/doi/10.1145/2882903.2882927},
        year = {2016}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
1,468 Towards a Learning Optimizer for Shared Clouds 2019 VLDB 0.00010686496
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Outgoing Citations (Sorted by Pagerank)

Showing 13 of 13 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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