服装企业包装订单分配排序优化模型及其快速非支配遗传算法求解

为解决纺织服装生产企业包装出货过程中在包装订单分配与排序时存在的分配方案不合理、拖期时间长等问题,在考虑包装线机器分配及机器调整时间约束的情况下,建立以最小化最大完成时间和拖期时间为目标函数的包装订单分配排序两目标优化数学模型,并采用基于参考点的快速非支配遗传算法对模型进行求解,然后对优化解进行解码输出优化方案。通过该模型与算法求解相关企业的具体算例,结果表明:该模型输出结果缩短了最大完成时间,有效地控制了拖期,几种优化方案的平均最大完成时间相较于按交货期优先规则的方案缩短了4.7%,且所有方案的总拖期均小于4 h。研究成果在提升纺织服装生产企业的包装出货效率方面具有良好的应用与推广价值。

Optimization modeling for packaging order allocation for garment enterprises and solution finding using non-dominated genetic algorithm

In order to solve the problems of irrational task allocation scheme and long delay time in order allocation and sorting in the packaging and delivery process of garment manufacturers, a two-objective optimization mathematical model for packaging order allocation and sorting with maximum completion time and tardiness as objective functions was established taking into account for the constraints to machine allocation and machine adjustment time of the packaging line. A reference-point-based multi-objective evolutionary algorithm was used to solve the model before decoding the optimized solution and output the optimized scheme. This model was employed to solve a specific problem encountered by an enterprise, the results demonstrate that the new model is able to shorten the maximum completion time and can effectively control the delay. The average maximum completion time of several optimization schemes is 4.7% shorter than that of the earliest due date rule schemes, and the total delay time of all schemes is less than 4 hours. The research findings are of good application value in improving the packaging and shipping efficiency of garment manufacturers.