github.com
> Is re-planning routes for regenerative braking solvable with the Modified Snow Plow Problem (variation on TSP Traveling Salesman Problem), on a QC Quantum Computer; with Quantum Algorithmic advantage due to the complexity of the problem?
FWIU the Modified Snow Plow Problem is a variant of TSP the Traveling Salesman Problem which takes topological grade into account; only plow downhill.
Regenerative braking charges on downhills.
TSP can be implemented with quantum algorithms for a quantum computer.
There could be a call for and/or an ml competition for QC algos for TSP and similar:
> - QISkit tutorials > Max-Cut and Traveling Salesman Problem: docs/tutorials/06_examples_max_cut_and_tsp.ipynb: https://qiskit.org/ecosystem/optimization/tutorials/06_examp...
Quantum Algorithm Zoo probably lists existing quantum algorithms that might be useful for this application
The screenshot shows a network that is not optimal. I would guess the solution using existing nodes is A-E-C-B and D-E.
Do you generate Steiner Points (additional nodes) that minimize the network length?
In the screenshot example, I guess a better solution would be A-E-C with 2 Steiner Points at the feet of the perpendiculars from B and D to the line C-E.
https://en.wikipedia.org/wiki/Steiner_point_(computational_g...