Knapsack Problem variants of QAOA for battery revenue optimisation

Understand

We implement two Quantum Approximate Optimisation Algorithm (QAOA) variants for a battery revenue optimisation problem, equivalent to the weakly NP-hard Knapsack Problem.

• Both approaches investigate how to tackle constrained problems with QAOA.
• A first 'constrained' approach introduces a quadratic penalty to enforce the constraint to be respected strictly and reformulates the problem into an Ising Problem.
• However, simulations on IBM's simulator highlight non-convergent results for intermediate depth ($ p\leq 50$).