Research On Dynamic Scheduling Of Garment Hanging Production Line Based On Genetic Algorithm

Since the 21 st century,the competition in the clothing industry is becoming increasingly fierce.The plan-driven mode of the standardized and large-scale production can barely satisfy the diversified demand of nowadays fashion market.Garment enterprises are developing the capacity of small batch order production to adapt to various changes in demand,shorter product life cycle in garment mass customization and improve inventory turnover rate,which puts forward higher requirements of the management ability in garment industry.At present,the flexibility and intelligence of garment manufacturing is relatively low,which can hardly deal with the uncertain delivery time of order and eliminate the bottlenecks of production in time,which leads to the failure to complete the order tasks on time.Thererfore,an intelligent scheduling mechanism is urgently needed to improve the real-time capability and flexibility of garment manufacture.The aim of this paper is to improve the dynamic scheduling mechanism for mass customization production.Based on the cloth hanging production,the study is develop in the following areas:Firstly,a dynamic scheduling model was established to minimize the completion time and equipment waiting time considering the constraint conditions of technological route,task complexity degree,equipment capacity,skills of people and the difference of technology when process orders,based on the investigation of a cloth hanging production line.Secondly,several dynamic scheduling methods was reviewed and an adaptive dynamic scheduling model of the hanging production line was proposed based on the traditional rolling scheduling strategy that driven by fixed cycle to slove the uncertain of the orders completion time and bottleneck happened place.To improve the efficiency of the production and the utilization of the equipment in each scheduling cycle,an non-dominanted genetic algorithm was designed based on the double layer codeing of the process and the equipment.Finally,to validate the superiority of proposed adaptive dynamic scheduling mode,the dynamic arrival process of customized orders in 21600 s was simulated based on the real enterprise data and the mathematical statistics methods.The result shows that compared with traditional dynamic scheduling that driven by fixed cycle(T =3600s),the completion time and the utilization rate of the proposed adaptive dynamic scheduling mode improve 4.9% and 18.2%,respectively;compared with cycle time(T= 7200s)the proposed method improve 18.63% and 30.97%,respectively.