Empirical tests show QUBO-SA and QAOA-inspired schedulers lose feasibility beyond 10-15 tasks while MILP, CP-SAT, GA and HEFT remain robust on the same instances.
A novel approach for solving constrained optimization problems with the quantum approximate optimization algorithm,
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An Empirical Evaluation of Quantum-Inspired QUBO Methods for Heterogeneous HPC Workflow Mapping and Scheduling
Empirical tests show QUBO-SA and QAOA-inspired schedulers lose feasibility beyond 10-15 tasks while MILP, CP-SAT, GA and HEFT remain robust on the same instances.