Optimal routing of multiple autonomous underwater vehicles through evolutionary programming

Evolutionary programming is all inductive reasoning process wherein randomness is selectively incorporated to build a logic that meets the challenges posed by the environment. A demonstration of evolutionary optimization in the domain of routing multiple autonomous underwater vehicle (AUVs) is indicated. A series of experiments of increasing complexity were designed to evaluate the potential of evolutionary programming for AUV routing. In the experiments, the evolutionary algorithm was given no knowledge about the problem itself, only information concerning the relative worth of its proposed solutions. It is evident from the experimental results that sophisticated genetic operators are not required to ensure successful adaptation. The experiments only involved two-dimensional routings with relatively simple constraints. The experiments were performed off-line, that is, an entire solution to the routing problem at hand was generated assuming a fixed environment