  The use of D-Wave's Leap Hybrid solver is demonstrated here in solving a
Knapsack optimization problem: finding meal combinations from a fixed menu that
fit a diner's constraints. This is done by first formulating the optimization
problem as a Constrained Quadratic Model (CQM) and then submitting it to a
quantum annealer. We highlight here the steps needed, as well as the
implemented code, and provide solutions from a Chicken and Waffle restaurant
menu. Additionally, we discuss how this model may be generalized to find
optimal drug molecules within a large search space with many complex, and often
contradictory, structures and property constraints.
