【摘要】 针对单一优化算法存在早熟现象明显、收敛速度慢、寻优精度不足、对初始种群敏感等缺陷,提出以"扬长避短"为理念的混行算法.利用遗传算法(GA)与人工鱼群算法(AFSA)的全局收敛性、解析法的精确性,构建一种将并行模块与二次优化模块相串联的模型,形成混行算法.通过对并行模块的优化结果进行二次优化,使其符合工程应用要求.将上述模型应用于32 t/22.5 m的桥式起重机主梁轻量化设计中,结果表明,该算法对截面的最小化优化是成功的.更多还原

【Abstract】 In view of the shortcomings of a single optimization algorithm,such as premature phenomenon,slow convergence rate,lack of optimal precision and sensitivity to initial population,this paper proposes a hybrid algorithm based on the idea of "avoiding weaknesses".By using the global convergence and analytic accuracy of genetic algorithm(GA) and artificial fish swarm algorithm(AFSA),a model of parallel module and two times optimization module is constructed to form a mixed-line algorithm.The optimization results of parallel modules are optimized two times to meet the requirements of engineering application.Applying the above model to the lightweight design of the main girder of the 32 t/22.5 m bridge crane,the results show that the algorithm is successful in minimizing the cross-sectional optimization.更多还原