Multi-target Collaborative Combat Decision-Making by Improved Particle Swarm Optimizer

摘要

A decision-making problem of missile-target assignment with a novel particle swarm optimization algo-rithm is proposed when it comes to a multiple target collaborative combat situation.The threat function is estab-lished to describe air combat situation.Optimization function is used to find an optimal missile-target assignment. An improved particle swarm optimization algorithm is utilized to figure out the optimization function with less pa-rameters,which is based on the adaptive random learning approach.According to the coordinated attack tactics, there are some adjustments to the assignment.Simulation example results show that it is an effective algorithm to handle with the decision-making problem of the missile-target assignment(MTA)in air combat.