基于遗传算法的服装大规模定制生产线平衡优化

为解决大规模服装定制混流生产过程中出现的产品在线时间长、节拍不均衡、生产成本高等问题,首先对大规模服装定制复杂生产线特点及问题进行分析,构建了具有多子组管理、多目标寻优、服装单件定制的混合生产线平衡优化模型;然后利用矩阵原理对工序进行约束编码,并给出从工序到工位转换的解码算法;接着通过轮盘赌选择、两点交叉和单点变异、多目标适应度函数等算法设计实现了混流生产线的生产平衡;最后以大规模西服定制生产线为例,借助MatLab技术进行编程实现。结果表明,各组子生产线中编制效率最高可达93.93%,总生产线平均编制效率为85.77%,满足企业工序编制要求,验证了本文模型可有效解决大规模服装定制生产线的生产平衡问题。

Balance optimization of clothing mass customization production line based on genetic algorithm

In order to solve the problems of long product online time, unbalanced tempo, and high production cost in the production process of mass-customized mixed assembly line, the research reported in this paper first analyzed the characteristics and problems of the complex production line of clothing mass customization, and constructed a hybrid production line balance optimization model with multi-subgroup management, multi-objective optimization and clothing single-piece customization. The research used the matrix principle to constrain the coding of the process, and established a decoding algorithm for station conversion. As a result, production balance of the entire mixed pipeline was achieved using the designed algorithms for roulette selection, two-point crossover and single-point mutation, and multi-objective fitness function. Mass customization production line of suits was taken as an example to demonstrate the use of MatLab technology for programming. The results show that the highest preparation efficiency of all sub-production lines can reach 93.93%, the average preparation efficiency of the total production line is 85.77%, which meets the requirements of the process planning set by the collaborating enterprise. It is indicated that the model established in this research can effectively solve the production balance problem of the mass customization production line.