A Method of Firepower Assignment with Multi Launchers and Multi Weapons Based on Improved MOQPSO Algorithm
PENG Guang
FANG Yangwang
CHAI Dong
PENG Weishi
Abstract：Aimed at the problem that the multi?obj ective particle swarm optimization algorithm in finding the solution easily gets into the local optimum by using the MOPSO algorithm to deal with the weapon tar-get assignment,an improved multi?objective quantum?behaved particle swarm optimization (MOQPSO) algorithm is proposed.First,the improved MOQPSO algorithm is applied in solving the optimization mod-el of firepower assignment with multi?launcher and multi?weapon by adj usting encode mode,modifying the position update formulas,introducing Gaussian mutation,and updating the external archives.Next,the improved MOQPSO and MOPSO algorithm are adopted to solve two battle suppositions with different scale.Finally,the convergence of the multi?obj ective optimization model is compared with that of the sin-gle obj ective optimization model.The simulation results indicate that the computation speed of the im-proved MOQPSO is about six times faster than that of the MOPSO,and the convergence of the Pareto so-lutions is high in precision and the diversity is even more,and the effectiveness and superiority of the im-proved MOQPSO algorithm are verified.
Keywords：multi?launcher and multi?weaponfirepower assignmentmulti?obj ective quantum?behaved par-ticle swarm optimizationPareto front
Publication Date：2016-01-01
Pages：6( 25-30 )