Genetic algorithm with simulated annealing for laser antimissile optimization

Abstract

A dynamical laser antimissile problem is solved based on genetic algorithm with simulated annealing considering the real time application. When faced with multiple attacking targets, it is clearly important for the laser antimissile system to determine the sequence of the attacking targets to be intercepted so that the maximum attacking targets are destroyed. Conceptually, this laser antimissile problem can be seen as a dynamical traveling salesman problem, which is much harder than a pure traveling salesman problem. There are many barriers for finding the global optimal solution, especially when the number of the targets is greater than six. The genetic algorithm has the capability of searching in wider space. While the simulated annealing algorithm can jump from the local optimal solution. Therefore, the combination of the genetic algorithm and the simulated annealing algorithm has their merits. Taking ten targets as an example, the simulation results show that the proposed algorithm has the better property and can be used in the real application. © 2010 IEEE.