Attack allocation plan optimization of fire control based on two-stage ordinal optimization model

Attack allocation plan optimization of fire control is a simulation optimization problem with multi-input parameters. For traditional optimization algorithms involve massive calculation and are time consuming, a two-stage ordinal optimization model is proposed. The launching success probability of air-to-air missile is used as the criterion to evaluate the plan. The optimization strategy includes crude and fine evaluation optimization. First, a crude evaluation model based on the particle swarm optimization and genetic programming (PSO-GP) algorithm is established. And all the allocation plans are rapidly evaluated by the crude model to get the high quality solution set. Second, a more refined crude model is established to improve the accuracy of the high-quality solution set step by step. Then the optimal allocation plans are obtained by evaluating the final high-quality solution set with the simulation model. Numerical simulation analysis shows the effectiveness and feasibility of the proposed model.