摘要
Abstract
To overcome the inherent defects of stagnation and premature convergence in standard genetic algorithm, the simulated annealing algorithm with strong local search capability is integrated into the algorithm, annealing stretching is applied to fitness function, annealing treatment is adopted for acceptation operator, and meantime, self-adaption mechanism is added to improve crossover rate and mutation rate of standard genetic algorithm. Especially adjustment of mutation rate can change the mutation rate automatically according to size of individual fitness and different evolutionary status so as to strengthen algorithm's ability to break away from local optimum solution. In the end, self-adaption annealing genetic algorithm is formed for crane main girder optimization. Verification by example and comparison with the standard genetic algorithm shows that both convergence rate and global convergence of the new algorithm improve a lot under the premise of better convergence results.关键词
起重机/箱形梁/自适应退火遗传算法/优化设计/全局收敛性Key words
crane/box girder/self-adaption annealing generic algorithm/optimal design/global convergence分类
机械制造
