Solving the Multisensor Resource Scheduling Problem for Missile Early Warning by a Hybrid Discrete Artificial Bee Colony Algorithm

Aiming at the problem of multisensor resource scheduling in missile early warning operation, a decomposition strategy for tasks under cooperative detection is proposed. Taking benefit factor, target threat and handover factor as fitness function, we establish sensor-subtask assignment (SSA) model propose hybrid discrete artificial bee colony (HDABC) algorithm to solve optimal solution SSA model. The HDABC has following improvements: initialization stage, sensor-subtask-based coding method designed reduce dimension, heuristic rules are used obtain excellent populations improve convergence speed; employed onlooker food source update based on differential mutation (DDM) operation proposed searchability algorithm, sorting-based adaptive probability (SAP) selection applied enhance global search local optimization capacities. Simulation experiments were carried out scenarios different scales. Experimental results showed that can schemes had better solving performance when model, especially medium-scale large-scale scenarios.