关键词: 粒子群算法, 拒绝法, 罚函数法, 种群多样性保持策略, 配方优化数学模型

Abstract: Characteristic signal of solid propellant combustion more and more becomes an important factor to restrict missile stealth characteristics and guidance precision development. In order to solve the problem of long formulation design cycle to reduce the characteristic signal, which is caused by traditional experimental method, Particle Swarm Optimization Algorithm（PSOA） is studied to find the optimal design scheme of solid propellant formulations to reduce characteristic signal. In the process, the rejection method, the penalty function method and the strategy of keeping population diversity are used to improve standard PSOA properly. It solves the nonlinear constraint problem, overcomes the defects of algorithm to fall into local optimum easily and improves global search ability. Establishment of the formulation optimization model and simulation results show that in the aspect of reducing characteristic signal, improved PSOA is superior to some other intelligent algorithms, such as, improved genetic algorithm, standard particle swarm optimization and so on， and it can also shorten the formulation design cycle.

Key words: Particle Swarm Optimization Algorithm（PSOA）, reject method, penalty function method, strategy of keeping population diversity, formulation optimization model