基于混合遗传算法在印染车间生产调度研究与应用  

Research and application of hybrid genetic algorithm in printing and dyeing workshop

作　　者：何宇翔 楚建安[1] 李珍 苟乐 赵春涛 He Yuxiang;Chu Jian'an;Li Zhen;Gou Le;Zhao Chuntao(School of Electronics and Information,Xi'an University of Technology,Xi'an 710048,China)

机构地区：[1]西安工程大学电子信息学院,西安710048

出　　处：《国外电子测量技术》2020年第12期141-146,共6页Foreign Electronic Measurement Technology

摘　　要：针对遗传算法在印染车间生产调度时收敛性与全局搜索能力不能兼顾等问题,提出了一种基于混合遗传算法的初始种群生成方法。通过对生产车间调度进行数学建模、对遗传算法的初始种群进行改进,以海明距离的方式均匀展开,再将模拟退火算法的思想融入到遗传算法变异操作中,提高遗传算法在印染车间调度问题的性能。最后,将传统遗传算法与改进的混合遗传算法进行仿真实验对比。通过仿真实验证实了此算法拥有更好的收敛性,且在车间生产调度问题上具有高效性和精确性。Aiming at the problem that genetic algorithm cannot balance the convergence and global search ability in production scheduling of printing and dyeing workshop,an initial population generation method based on hybrid genetic algorithm is proposed.Through mathematical modeling of the production workshop scheduling,the improvement of the initial population of the genetic algorithm,uniform expansion in the way of Hamming distance,and then the idea of the simulated annealing algorithm is integrated into the genetic algorithm mutation operation to improve the genetic algorithm in the printing and dyeing workshop scheduling the performance of the problem.Finally,the traditional genetic algorithm and the improved hybrid genetic algorithm are compared with simulation experiments.Simulation experiments have confirmed that this algorithm has better convergence,and it is efficient and accurate in workshop production scheduling problems.

关 键 词：海明距离 遗传算法 模拟退火算法 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]