The quadratic assignment problem (QAP) is a notoriously difficult combinatorial optimization problem with optimally solvable instances of the QAP being relatively small. For most instances, heuristic techniques are necessary to provide a solution in a reasonable amount of time. Through the use of gradient information from the objective function, I develop a heuristic algorithm to find locally optimal solutions to instances 100 times as large as commonly studied in a fast and efficient way.