优化设计在工程设计中，可以从大量可行的设计方案中寻找到最优的方案，因而提高设计质量。本文研究了粒子群优化算法的基本原理，分析了其特点，充分利用粒子群算法的全局搜索和局部搜索相结合的优点，将其应用于盖板的优化设计，以盖板轻量化为研究目标，以满足强度、刚度、稳定性等为约束条件，建立盖板优化的数学模型，用粒子群算法对变量进行求解。最后将粒子群优化的结果和其他几种优化方法相比较，基于粒子群优化的盖板设计得到了最好的优化方案。 In engineering design, optimization design finds the optimal solution from a wide variety of design methods, thereby improving the design quality. This paper studies the basic rationales of Particle Swarm Optimization (PSO) and analyzes its characteristics. We aim to reduce the weight of cover plate while maintaining its strength, stiffness and stability. After setting up a mathematical model of optimization design of cover board, we use PSO to solve the variables. Due to the advantage of combining both global search and local search, the application of PSO on design optimization of cover plate achieves a better result compared to several other constrained optimization methods.
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机译：优化设计在工程设计中，可以从大量可行的设计方案中寻找到最优的方案，因而提高设计质量。本文研究了粒子群优化算法的基本原理，分析了其特点，充分利用粒子群算法的全局搜索和局部搜索相结合的优点，将其应用于盖板的优化设计，以盖板轻量化为研究目标，以满足强度、刚度、稳定性等为约束条件，建立盖板优化的数学模型，用粒子群算法对变量进行求解。最后将粒子群优化的结果和其他几种优化方法相比较，基于粒子群优化的盖板设计得到了最好的优化方案。 In engineering design, optimization design finds the optimal solution from a wide variety of design methods, thereby improving the design quality. This paper studies the basic rationales of Particle Swarm Optimization (PSO) and analyzes its characteristics. We aim to reduce the weight of cover plate while maintaining its strength, stiffness and stability. After setting up a mathematical model of optimization design of cover board, we use PSO to solve the variables. Due to the advantage of combining both global search and local search, the application of PSO on design optimization of cover plate achieves a better result compared to several other constrained optimization methods.
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