Publication2026
Quantum-Optimized Ride-Pooling for Urban Mobility Using QUBO and Hybrid Quantum-Classical Algorithms
- Industry, Innovation and Infrastructure
- Sustainable Cities and Communities
- Thriving and Sustainable Economy
The record
- Type
- Publication
- Date
- 1 January 2026
- Level
- National
- Journal
- 2026 5th International Conference on Power Control and Computing Technologies Icpc2t 2026
- Pages
- 7-12
- Published
- 1 January 2026
- DOI
- 10.1109/icpc2t68221.2026.11646237
- Scopus ID
- 105048794394
- Authors
- 6
- Open access
- No
- Citations
- 0
- International co-authorship
- No
- Co-author countries
- IN
Classification
Every label below carries the reasoning it was assigned on, the confidence band it was assigned in, and what produced it. The rubric is published.
UN Sustainable Development Goals
11.2 Provide access to safe, affordable, accessible and sustainable transport systems for all
Quantum-optimized ride-pooling using QUBO and hybrid algorithms reducing travel distances by 18.3% and fuel consumption by 7.96% for urban transportation.
- High confidence
- The subject matter is a strong and direct inference from the record type, the funding or organising body, or the programme context, even where the title alone is thin. Example: an ICMR-funded project against SDG 3, on the strength of the agency.
- Judged
- Judged against the published classification rubric, under the rubric and prompt versions recorded with the run that produced it.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
9.5 Enhance scientific research, upgrade technological capabilities, and increase researchers and R&D spending
Hybrid quantum-classical computing methodology for solving complex combinatorial optimization in intelligent urban mobility systems.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Viksit Bharat @2047
vb-2 Thriving and Sustainable Economy
Derived through the seeded SDG-to-Viksit-Bharat crosswalk from the primary SDG 11 label. Quantum-optimized ride-pooling using QUBO and hybrid algorithms reducing travel distances by 18.3% and fuel consumption by 7.96% for urban transportation.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Each label above carries the instrument and the version that produced it. How each classification is reached.
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- Source rows resolved into this record
- 1
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Citing this record
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KIIT Deemed to be University. “Quantum-Optimized Ride-Pooling for Urban Mobility Using QUBO and Hybrid Quantum-Classical Algorithms”. Kortex.
