关键词: 粒子群算法, 离散变量, 可行域, 优化设计, 齿轮系

Abstract: Aiming at the constrained discrete optimization of a gear train featuring a large solution space with a narrow feasible region，two new strategies based on Particle Swarm Optimizer （PSO） are introduced to deal with constraints and discrete variables.In order to reduce the number of algorithm parameters，the formula of updating particle’s velocity in normal PSO is also modified.Then，the algorithm is applied to the discrete optimization problem.Compared with the approaches in the relative literature，the success rate of the algorithm to find feasible solutions is higher，and at the same time it obtained better “best” solutions and mean result without either requiring transformation of the problem or reliance on the designer’s interaction.The results show that the algorithm is simple and easy to implement yet effective，and it have an important reference value to the solving of similar optimal design problems.

Key words: Particle Swarm Optimizer（PSO）, discrete variable, feasible region, optimal design, gear train