Ant Colony Algorithm For Solving The Weapon-Target Assignment Problem

Weapon-Target Assignment Problem is a typical optimization problem, which requires finding proper engagement of weapons to targets, aiming at minimizing the expected damage of own force asset. With the development and wide application of weapons and equipment with information technology, the weapon-target assignment problem has consequently received a great deal of attention in recent years. This paper emphasizes a research on the solution of WTA based on ant colony algorithm.Firstly, based on the analysis of the existing methods and recent development of WTA problem, the author classify the WTA problem from different perspectives, saying static WTA and dynamic WTA, perspectively defining them and modeling them. As a special case, the constructing process of the attack strategy model in intelligent mine field is further discussed. The distance, angle and velocity between landmine and tank are combined together and carefully analyzed. As a result, the target funtion of optimizing intelligent mine field attack strategy is founded.After confirmation of WTA model and algorithm, this article introduces the idea of particle colony algorithm into the search of ant colony algorithm. Simulation results verify the effectiveness of the new improved algorithm, the improved algorithm is with higher solving accuracy, faster convergence speed, and superior time performance compared with basic ant colony algorithm. To assure the stability of the new improved ant colony algorithm, this paper gives the principle of the parameter selection from the discussing of the key parameters. Also the paper gives implementation steps of new improved algorithm in solving WTA problems, and obtains specific weapons-target optimal allocation schemesolves in WTA examples. At last, the experimental verification of the strategy-making model of the intelligent mine field is given.