A Decisions Query Language (DQL): High-Level Abstraction for Mathematical Programming over Databases
Summary: DQL unifies mathematical programming with database queries for decision optimization over data. Tight integration reduces impedance mismatch and enables more efficient evaluation than loosely coupled systems; makes OR-style optimization accessible to DB programmers with no OR background; demonstrated in an emergency scenario. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Alexander Brodsky (George Mason University)
- 2. Mayur M. Bhot (George Mason University)
- 3. Manasa Chandrashekar (George Mason University)
- 4. Nathan E. Egge (George Mason University)
- 5. X. Sean Wang (University of Vermont)
BibTeX Citation
@inproceedings{brodsky_sigmod09,
title = {{A Decisions Query Language (DQL): High-Level Abstraction for Mathematical Programming over Databases}},
author = {Brodsky, Alexander and Bhot, Mayur M. and Chandrashekar, Manasa and Egge, Nathan E. and Wang, X. Sean},
series = {{SIGMOD} '09},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/1559845.1559981},
url = {https://dl.acm.org/doi/10.1145/1559845.1559981},
year = {2009}
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