In this paper the use of a Genetic Algorithm to solve a constrained vehicle routing problem is explored. The problem is two-dimensional with obstacles represented as ellipses of uncertainty surrounding each obstacle point. A route is defined as a series of points through which the vehicle sequentially travels from the starting point to the ending point. The physical constraints oftotal route length and maximum turn angle are included and appear in the fitness function. In order to be valid, a route must go from start to finish without violating any constraint. The effects that different mutation rates and population sizes have on the algorithm's computation speed and ability to find a high quality route are also explored. Finally, possible applications ofthis algorithm to the problem ofroute planning for cruise missiles are discussed.