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A genetic-algorithm-based optimization model for scheduling flexible assembly lines

机译:基于遗传算法的柔性装配线调度优化模型

摘要

In this paper, a scheduling problem in the flexible assembly line (FAL) is investigated. The mathematical model for this problem is presented with the objectives of minimizing the weighted sum of tardiness and earliness penalties and balancing the production flow of the FAL, which considers flexible operation assignments. A bi-level genetic algorithm is developed to solve the scheduling problem. In this algorithm, a new chromosome representation is presented to tackle the operation assignment by assigning one operation to multiple machines as well as assigning multiple operations to one machine. Furthermore, a heuristic initialization process and modified genetic operators are proposed. The proposed optimization algorithm is validated using two sets of real production data. Experimental results demonstrate that the proposed optimization model can solve the scheduling problem effectively.
机译:本文研究了柔性装配线(FAL)中的调度问题。提出了针对该问题的数学模型,其目标是最小化拖延和提前处罚的​​加权总和,并平衡FAL的生产流程,该流程考虑了灵活的作业分配。开发了一种双层遗传算法来解决调度问题。在该算法中,提出了一种新的染色体表示,通过将一个操作分配给多台机器以及将多个操作分配给一台机器来解决操作分配问题。此外,提出了启发式初始化过程和改进的遗传算子。使用两组实际生产数据验证了所提出的优化算法。实验结果表明,所提出的优化模型能够有效解决调度问题。

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