Cooperative weapon-target assignment based on multi-objective discrete particle swarm optimization-gravitational search algorithm in air combat

An air combat weapon-target assignment (WTA) model based on multi-objective decision theory with a hybrid evolutionary multi-objective optimization algorithm solver was proposed. Air combat is a multi-stage process of attack-defense countermeasure, existing WTA models are based on disposable fully allocated assignment without considering the missile consumption, which does not conform to the actual air combat process. The minimum of total expected remaining threats and total consumption of missiles were selected as two objectives functions of the multi-objective decision model, with the premise of reaching damage threshold. The hybrid multi-objective discrete particle swarm optimization-gravitational search algorithm (MODPSO-GSA) was proposed to handle the model, which possesses stable global search capacity and promises to converge to Pareto frontier. A Pareto optimal solution set with damage threshold met can be obtained, which offers decision reference to the commander. Simulation results verify that the model is of advantage and the proposed MODPSO-GSA is effective. ©, 2015, Beijing University of Aeronautics and Astronautics (BUAA). All right reserved.