具有工作站数量约束的多人工作站混合装配线平衡问题研究

Research on the Multi-manned Mixed-model Assembly Line Balancing Problem with the Workstation Quantity Constraint

针对装配线设计或改造过程中存在的因场地或成本原因导致的工作站数量不易变更的问题,研究了节拍已知情况下,具有工作站数量约束的多人工作站混合装配线平衡问题,建立以装配线总人数最小、工人负荷量标准差最小、各产品在各工作站装配时间与节拍之间的标准差最小为目标的数学模型,设计了一种结合差分进化的多目标混合遗传算法对该问题求解。通过案例计算以及与其他算法的对比分析表明,本文算法在收敛性和综合性能方面优于NSGAII和DEMO,在装配线人数和工人负荷标准差方面优于Roshani和Nezami提出的算法。

Workstations of some assembly line are not easy to change in the process of design and upgrading because of space or cost limit.The multi-manned mixed-model assembly line balancing problem with the workstation quantity constraint is studied under the condition of known cycle time.A mathematical model of multi-manned mixed model assembly line balance problem is established with minimizing objectives.These objectives include total number of assembly line workers,standard deviation of workers’load and sum of standard deviation between assembly time of different products and cycle time.A hybrid multi-objective genetic algorithm combined with differential evolution is designed to solve the problem.The model and algorithm prove to be valid by calculating the example and comparing with other algorithm.The algorithm is superior to NSGAII and DEMO in convergency and comprehensive performance,and stays ahead of the method which is proposed by Roshani and Nezami in total number of assembly line workers and standard deviation of workers’load.