改进遗传算法在车间调度问题中的应用  

Application of improved genetic algorithm in job-shop scheduling problem

作　　者：杨帆 方成刚[1] 洪荣晶[1] 吴伟伟[2] YANG Fan;FANG Chenggang;HONG Rongjing;WU Weiwei(School of Mechanical and Power Engineering,Nanjing Tech University,Nanjing 211800,China;College of Mechanical Engineering,Yangzhou University,Yangzhou 225000,China)

机构地区：[1]南京工业大学机械与动力工程学院,江苏南京211800 [2]扬州大学机械工程学院,江苏扬州225000

出　　处：《南京工业大学学报（自然科学版）》2021年第4期480-485,共6页Journal of Nanjing Tech University(Natural Science Edition)

基　　金：国家自然科学基金(51635003);江苏省科技成果转化专项资金项目(BA2017099)。

摘　　要：为了解决遗传算法在求解部分柔性作业车间调度问题中寻优能力较弱以及加工时间和机器矩阵编写繁琐的问题,提出一种新的交叉操作和基于元胞数组的解码方式,在遗传操作的解码操作步骤加入随机算子,以保证机器选择的随机性;在选择操作步骤中引入保优策略避免优质解的丢失,加快种群收敛速度;采用一种新的单点交叉方式,增强算法的寻优能力;以最大完工时间最小为目标函数对算例进行对比仿真,结果证明了所提出算法的可行性和优越性。In order to solve the weak optimization ability of genetic algorithm(GA)for the partial flexible job-shop scheduling problem(P-FJSP)and the complicated problem of time and machine matrix,a new crossing operation and a decoding method based on the cell array were proposed.The random operator was added to the decoding operation of the genetic operation to ensure the randomness of the machine selection.The elitist strategy was introduced to avoid the loss of high quality solution and speed up the convergence speed of the population.A new single point crossing method was used to enhance the optimization ability of the algorithm.Results showed that the improved algorithm was feasible and superior with the maximum completion time minimum as the objective function.

关 键 词：部分柔性作业车间调度 改进遗传算法 元胞数组 交叉操作 

分 类 号：TP278[自动化与计算机技术—检测技术与自动化装置]