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首页> 外文期刊>IEEE Transactions on Robotics >A Genetic-Algorithm-Based Optimization Model for Solving the Flexible Assembly Line Balancing Problem With Work Sharing and Workstation Revisiting
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A Genetic-Algorithm-Based Optimization Model for Solving the Flexible Assembly Line Balancing Problem With Work Sharing and Workstation Revisiting

机译:基于遗传算法的工作共享与工作站重访解决柔性流水线平衡问题的优化模型

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摘要

This paper investigates a flexible assembly line balancing (FALB) problem with work sharing and workstation revisiting. The mathematical model of the problem is presented, and its objective is to meet the desired cycle time of each order and minimize the total idle time of the assembly line. An optimization model is developed to tackle the addressed problem, which involves two parts. A bilevel genetic algorithm with multiparent crossover is proposed to determine the operation assignment to workstations and the task proportion of each shared operation being processed on different workstations. A heuristic operation routing rule is then presented to route the shared operation of each product to an appropriate workstation when it should be processed. Experiments based on industrial data are conducted to validate the proposed optimization model. The experimental results demonstrate the effectiveness of the proposed model to solve the FALB problem.
机译:本文研究了工作共享和工作站重新访问之间的灵活流水线平衡(FALB)问题。提出了问题的数学模型,其目的是满足每个订单的期望周期时间,并最大程度地减少组装线的总闲置时间。开发了一个优化模型来解决所解决的问题,该模型涉及两个部分。提出了一种具有多父级交叉的双层遗传算法,以确定对工作站的操作分配以及在不同工作站上处理的每个共享操作的任务比例。然后提出启发式操作路由规则,以在应处理每个产品时将每个产品的共享操作路由到适当的工作站。进行了基于工业数据的实验,以验证所提出的优化模型。实验结果证明了该模型解决FALB问题的有效性。

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