Abstract:

An improved multi-objective particle swarm optimization （MOPSO) algorithm is proposed, which adjusts constraint conditions, modifies the velocity and position update formulas for the multi-objective programming model of weapontarget assignment optimization. The algorithm can obtain a non-inferior solution to form the Pareto front, which can reflect the effect of increased firepower unit on firing efficiency. Decisionmakers can find the final solution from the non-inferior subset solution according to their intention. Compared with the single objective function in the iterate evolution, the maximum value of the kill probability to enemy shows the same convergence performance and close maximum result, excluding the factor objective of the multi-objective programming model, which verifies the effectiveness of the MOPSO algorithm.