The mathematic model for Dynamic Joint Fire Distribution (DJFD) problem is presented, which considers over cooperation between weapons and sensors while assigning weapons to targets against a background of air formation attacking to surface mobile targets. The constraint space which comprises resource constraints, shifting firepower constraints, temporal constraints and spatial constraints is analyzed. An anytime algorithm based on decentralized cooperative auction is developed in the paper for the DJFD problem. The algorithm has two main advantages: (1) the algorithm can assign targets asynchronously and accept new targets for assignment during the allocation process, (2) the algorithm can get a better solution compared with the ones which assign targets synchronously. The feasibility and the validity of the algorithm are verified in simulation. At the end, further researches needed are discussed.

Anti-air weapons deployment optimization is a important researching of modern air defense combat, the paper propose method of anti-air position deployment of multi-types of anti-air weapons according to stand off attacking. Topography of position, intercept ability based on queuing theory are taken into account in the optimization model. For evolution algorithm, a memetic algorithm that hybridize genetic algorithm with hill climbing for solving this problem is put forward, proper crossover operator, and local search strategy are employed to improve performance of evolution procedure. Experiments results show that the memetic algorithm perform better and the optimization method is feasible and effective to solve the deployment optimization.