Systems
SYSTEM 001 · INDUSTRIAL AI & OPTIMIZATION
RESEARCHSOURCE VERIFIED
Energy-Aware Production Scheduling
TÜBİTAK 2209-A Applied Research Architecture
- ROLE
- Researcher (TÜBİTAK 2209-A)
- ENGINE
- MIP / Reinforcement Learning / QUBO
- TIMELINE
- 2025 - 2026
Examine how energy prices can be incorporated into production scheduling decisions through multiple optimization approaches.
Production scheduling and changing energy prices form a combined industrial optimization problem.
Outcomes
- Research accepted under the TÜBİTAK 2209-A program.
- Compared MIP, Reinforcement Learning, and QUBO in an energy-price-aware production scheduling context.
Stack
MIPReinforcement LearningQUBO