The improving hybrid algorithm on the target allocation

This paper analyses cultural genetic algorithm (CGA) combined with the reversal operation, and presents a specific hybrid optimization methodology which can address the problem of target assignment. The simulation results show that the probability of finding the global optimal solution and the convergence rate of the improved genetic algorithm based on cultural algorithm (CA) is obviously superior to that of the basic genetic algorithm (BGA) and cultural algorithm. Finally we get a better target assignment results; thus it provides a beneficial reference for addressing the problem of air defense deployment effectively.

I. Introduction

The purpose of the target allocation, with the principle of the target allocation, is to maximize the characteristics of a large variety of air defense weapons, which are distributed reasonably and effectively, and earn the smallest loss and the maximum lethality to defense our positions effectively in the complex air defense war of wide airspace, full time domain, all-round, multiple types of airplane, multi-wave. It is essential to seek the optimal solution of the target allocation, because the rationality of target allocation is closely related to the tactical effect and the play of battle effectiveness. This also has been a concern of many experts.