基于改进引力搜索算法的桁架结构优化设计

引力搜索算法是近几年提出的较有竞争力的群智能优化算法,然而,标准引力搜索算法存在后期收敛速度慢的缺点.为有效利用优化算法来解决结构优化的问题,提出一种改进的引力搜索算法(improved gravitational search algorithm,IGSA).通过引入Logistic映射,使GSA初始种群遍历整个搜索...

Optimization Design of Truss Structure Based on Improved Gravitational Search Algorithm

The gravitational search algorithm(GSA) is a competitive swarm intelligence optimization algorithm proposed in recent years. However,the standard gravitational search algorithm has the disadvantage of slow convergence in the later stage. In order to effectively solve the problem of structural optimization,an improved gravity search algorithm(IGSA) is proposed. By introducing Logistic mapping,the initial GSA population traverses the whole search space and improves the possibility of finding the optimal solution. Through the introduction of particle swarm optimization(PSO) information interaction mechanism,the particle speed and position can be dynamically adjusted by using the optimal position of individual particle history and the optimal position of population history,so that individual particles can move to the position with higher fitness value more quickly,and the search ability of the algorithm can be strengthened. Six classical test functions are optimized,and the results show that the improved algorithm has fast convergence speed,high convergence accuracy,high stability and strong ability to jump out of the local optimal solution. IGSA and GSA are used to optimize the size of the space truss of bar 72. Compared with other algorithms,the results show that the number of iterations of the optimal value obtained by IGSA is significantly reduced,and the optimal solution obtained is obviously superior to the general algorithm.