At present, the traditional optimization algorithms are frequently adopted to the optimization design for crane metal structures. However, those algorithms are generally impacted by such problems as analytical requirements for objective functions, local optimum or time-consuming computation. Due to few adjustable parameters without analytical requirements, a novel optimization algorithm, I. E. The particle swarm optimization algorithm based on swarm intelligence, is successfully applied in many fields. In this study, this algorithm is used for crane girder design. From example results,it is found that the optimization speed,besides optimization performance,is significantly enhanced by comparing with the grid algorithm.%现阶段起重机金属结构的优化设计一般都采用传统的优化算法,但传统算法普遍存在或对目标函数有解析性要求、或易陷入局部最优、或耗时较长的问题.微粒群优化算法是一种基于群体智能的新型优化算法,它可调参数少、对解析性无要求,已成功应用于多种领域.将微粒群算法应用于起重机主梁的优化中,经实例验证,在保证优化性能的前提下,基于微粒群算法的设计方法与网格算法相比,优化速度显著提升.
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