The planning of snow removal routes is complicated by the fact that the amount it snows, and thus the amount of resources, that is, vehicles, needed to clear it, varies from year to year. This variation has created a demand for a way to quickly generate efficient snow removal plans that take the resources that are available into account. In this report we describe the development of an ad hoc heuristic algorithm that improves already existing feasible solutions to the snow removal problem. It accomplishes this by reassigning tasks from the vehicles with the longest tours to those with the shortest tours, followed by reordering their tasks to ensure that the solution remains feasible. This algorithm is meant to be implemented in a larger piece of software and it is tested on a set of pre-generated solutions for a given network and number of vehicles, including the best known ones. Over half of the previously best known solutions were improved by this algorithm.