天基拦截弹群动态多目标优化任务分配方法

Task assignment for space-based weapon platforms equipped with interceptor missiles to intercept hypersonic vehicles in near space is investigated. Firstly，considering that space-based interceptor groups can dynamically use fewer resources to maximize the total expected damage of enemy targets，resource constraints，task constraints and time window constraints are established. A multi-objective optimization model is formulated to address constraints related to resource availability，task requirements，and temporal windows. The model aims to maximize interception success probability，minimize interception costs，and reduce collaborative interception timing discrepancies. To support this，fast estimation methods are proposed for predicting interception probability，assessing flight vehicle threat levels，and estimating remaining flight times. Subsequently，a dynamic task allocation algorithm is developed based on a multi-factor evolutionary approach. Simulation experiments，conducted under specific operational scenarios，validate the proposed model and algorithm. A comparative analysis against a discrete particle swarm optimization（DPSO）approach demonstrates the method’s effectiveness in dynamically and efficiently resolving task allocation challenges for space-based interceptor clusters.