面向大批量定制的产品族装配线平衡优化

Product Family Assembly Line Balancing for Mass Customization

针对产品族混合装配线平衡问题,建立了产品族装配线平衡模型,提出了一种改进的双种群遗传算法对产品族装配线进行优化。首先,通过研究分析产品族装配线的特点,重点考虑了作业之间的相关性;在遗传算法优化过程中,以最小化工作站数、最小化站间和站内负荷指数为优化目标,通过新译码方式弥补传统译码方式的不足,并在双种群中进行个体交换,提高了种群多样性,加快了算法的搜索速度和优化效率。最后,通过小型轮式装载机产品族装配线的平衡优化问题进一步验证了该算法的有效性和可行性。

Aiming at the balance problem of product family assembly line（PFAL）,a balancing model for PFAL is established.Firstly,through the characteristic analysis of PFAL,the correlation between the tasks is mainly considered. In the genetic algorithm,minimizing the number of stations,and minimizing the load indexes of between stations and within station are used as optimization objectives. Furthermore,a new decoding algorithm is proposed to make up for the lack of the traditional decoding method,and individuals in the two populations are exchanged. So the search speed of the algorithm is accelerated,which shows good performance in practice. Finally,the effectiveness and feasibility of the method are proved by optimizing assembly line balancing of loaders.