An Improved Genetic Algorithm for Target Assignment, Optimization of Naval Fleet Air Defense

As a weapon-target assignment problem (WTA), the fire-allocation of naval fleet air defense was studied and an optimal target assignment model was established. By combining the features of naval fleet anti-air combat, several classical assignment algorithms were discussed. To find global optimal results efficiently, an effective global search method i.e. genetic algorithms (GAs) was applied. However, this method still has disadvantages of slow convergence and poor stability in practical engineering. To solve these problems, an improved GA was proposed in terms of uniform creation of initial population, selection based on fitness scaling and self-adaptive parameters for genetic operators, etc. In the end, the steps for solving the optimal model were put forward, and satisfactory results have being obtained. It is shown that the present method can serve as a scientific and effective support for a decision maker in command automation of the naval fleet air defense combat