A problem that could possibly be quantum-optimized and an existing set of solutions: Scheduling
Optimize the scheduling problem better than e.g. SLURM and then generate a sufficient classical solution that executes in P-space on classical computers.
> Slurm uses a best fit algorithm based on Hilbert curve scheduling or fat tree network topology in order to optimize locality of task assignments on parallel computers.[2]
Additional applications and use cases: "Employee Scheduling" > "Ask HN: What algorithms should I research to code a conference scheduling app"
https://news.ycombinator.com/item?id=22589911
> [...] the Hilbert curve scheduling method turns a multidimensional task allocation problem into a one-dimensional space filling problem using Hilbert curves, assigning related tasks to locations with higher levels of proximity.[1] Other space filling curves may also be used in various computing applications for similar purposes.[2]
Optimize the scheduling problem better than e.g. SLURM and then generate a sufficient classical solution that executes in P-space on classical computers.
SLURM https://en.wikipedia.org/wiki/Slurm_Workload_Manager :
> Slurm uses a best fit algorithm based on Hilbert curve scheduling or fat tree network topology in order to optimize locality of task assignments on parallel computers.[2]
Additional applications and use cases: "Employee Scheduling" > "Ask HN: What algorithms should I research to code a conference scheduling app" https://news.ycombinator.com/item?id=22589911
> [Hilbert Curve Scheduling] https://en.wikipedia.org/wiki/Hilbert_curve_scheduling :
> [...] the Hilbert curve scheduling method turns a multidimensional task allocation problem into a one-dimensional space filling problem using Hilbert curves, assigning related tasks to locations with higher levels of proximity.[1] Other space filling curves may also be used in various computing applications for similar purposes.[2]