遗传算法在板式定制家具混合流水车间调度中的应用  

Application of Genetic Algorithm in Hybrid Flow Shop Scheduling of Panel Customized Furniture

作　　者：王迅 陈星艳[1,2,3] 陶涛 戴向东[1] 黄艳丽 欧阳周洲[1,4] 郝绍平[1,4] 詹秀丽 吕宙 Wang Xun;Chen Xingyan;Tao Tao;Dai Xiangdong;Huang Yanli;OuYang Zhouzhou;Hao Shaoping;Zhan Xiuli;LüZhou

机构地区：[1]中南林业科技大学,湖南长沙410004 [2]农林生物质绿色加工技术国家地方联合工程研究中心,湖南长沙410004 [3]木竹资源高效利用省部共建协同创新中心,湖南长沙410004 [4]欧派家居集团股份有限公司,广东广州510000

出　　处：《家具与室内装饰》2022年第11期1-5,共5页Furniture & Interior Design

基　　金：湖南省教育厅科学研究重点项目(19A522,20A509);湖南省财政科研专项(2050205)。

摘　　要：本文针对板式定制家具生产过程中相同并行机混合流水车间调度问题,以最早完工时间为目标,将具有良好的全局寻优能力和自适应优化特点的遗传算法应用于板式定制家具相同并行机混合流水车间调度中。并根据某板式定制家具企业实际的生产情况进行算法设计,在python软件上进行仿真实验,结合实际生产数据验证了算法的可行性。本文的仿真结果得到了一种新的优化调度方案,比传统的经验排序方法的总加工完成时间减少了37秒,生产效率提高了8.6%,对于优化板式定制家具相同并行机混合流水车间调度问题具有一定的借鉴意义。In order to address the same parallel machine hybrid flow shop scheduling problem in the production process of panel customized furniture, aiming at the earliest completion time, this paper applies the genetic algorithm with good global optimization ability and adaptive optimization characteristics to the same parallel machine hybrid flow shop scheduling of panel customized furniture. According to the actual production situation of a panel customized furniture enterprise, the algorithm is designed, and the simulation experiment is carried out on Python software. Combined with the actual production data, the feasibility of the algorithm is verified. The simulation results of this paper obtain a new optimal scheduling scheme, which reduces the total processing completion time by 37 seconds and improves the production efficiency by 8.6% compared with the traditional empirical scheduling method. It has a certain reference significance for optimizing the hybrid flow shop scheduling problem of the same parallel machine of panel customized furniture.

关 键 词：板式定制家具 遗传算法 混合流水车间调度 并行机 

分 类 号：TS664.1[轻工技术与工程]