Quantum Computing Experimentation with Amazon Braket

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Single-Objective Optimization Use Case

There are many classical tools available to solve optimization problems. For example, we can use genetic and simulated annealing algorithms directly on the problem. In addition, we can use linear programming or mixed integer linear programming methods, along with applications such as Gurobi and IBM C-Plex. In our case, we want to use quantum computers to solve optimization problems. To do this, we must convert our problem into a Quadratic Unconstrained Binary Optimization (QUBO) problem. Most real-world problems have integers and floating-point numbers, so this becomes a challenge because we must find a way to convert those into a series of binary variables that span our number range.

To show the process ...