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Large-Scale Multiple Query Optimisation with Incremental Quantum(-Inspired) Annealing

Summary: Incremental MQO framework that partitions large multiple-query optimization instances and reuses discarded partial solutions via dynamic search-steering, offloading subproblems to Fujitsu’s Digital Annealer (quantum-inspired annealing). Scales MQO to ~1,000 queries, substantially outperforms prior methods, and generalises to other DB workloads and future quantum accelerators. (summarized by gpt-5-mini on Feb 11 2026)

Paper ID
7328
Venue
SIGMOD
Year
2026
Pagerank
4.1945683e-05
Overall Rank
10,023 | 30.28%
DOI
10.1145/3749171

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Rank Citing Paper Year Venue Pagerank
10,283 Hybrid Mixed Integer Linear Programming for Large-Scale Join Order Optimisation 2026 VLDB 4.1945683e-05
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