摘要
针对云环境下制造资源优化配置模型求解问题,提出一种在花朵授粉算法基础上引入遗传算法和模拟退火算法的混合算法。首先,在花朵授粉算法的基础上引入遗传算法,用于前期种群初始化;然后,在迭代过程中加入模拟退火算法,避免陷入局部最优;最后,使用该混合算法求解实际问题,验证该算法处理资源配置问题的有效性和准确性。
An improved flower pollination algorithm is proposed for the solution of the optimal allocation model of manufacturing resources in the cloud environment.On the basis of the basic flower pollination algorithm,other algorithms are introduced—the genetic algorithm is used in the initial population initialization part,and the simulated annealing algorithm is added in the iterative process to avoid falling into the local optimum.Finally,the algorithm is used to solve actual problems,and the effectiveness and accuracy of the algorithm in dealing with resource allocation problems are verified.
作者
李贻婷
LI Yiting(Nanjing University of Information Technology,Nanjing 210000,China)
出处
《自动化与信息工程》
2022年第2期41-44,48,共5页
Automation & Information Engineering
关键词
云制造
资源配置
花朵授粉算法
遗传算法
模拟退火算法
cloud manufacturing
resource allocation
flower pollination algorithm
genetic algorithm
simulated annealing algorithm
