Route allocation for multiple snowplows using genetic algorithms

The road network of a small town is represented as a directed graph where each road junction is a vertex and each road segment (which has a length and a priority value) is a directed edge. We assume that there are several plows available to service the roads. We seek to compute an optimal allocation of routes to plows. Each route begins and ends at the same (depot) vertex. The union of all plow routes must cover every edge in the graph at least once. In addition, we wish to minimize the following parameters: total distance covered by all plows (thereby minimizing the deadhead miles), amount of variation in the mileage covered by individual plows (thereby dividing the workload equitably), number of u-turns and extent of priority misplacements. In this paper, we propose a Genetic Algorithms (GA)-based solution to compute a near-optimal route allocation and the minimization of other parameters simultaneously. This algorithm is based on our GA solution to the 1-plow problem reported earlier. We have developed a Java application that implements our algorithm. Our experiments with reasonably large graphs have yielded good solutions. These solutions are especially useful in snowplow routing for small towns, as plowing costs consume significant portions of the total municipal budgets of these communities. Most of the route planning in small towns is currently done manually and routes have evolved over time by experience. In these times of severe budget stress, route allocation using our approach can help in performing this essential service in a more efficient manner.