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Cigarette Production Scheduling by Combining Workflow Model and Immune Algorithm

机译:工作流模型与免疫算法相结合的卷烟生产调度

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Cigarette production scheduling is vital in improving production efficiency and reducing supply delay. In this paper, a workflow model combined with an immune algorithm is proposed to solve this problem for improving production efficiency. First, the problem is formulated as a mixed-integer quadratically constrained programming model. Afterwards, the problem is transformed into a workflow resource allocation one. Based on this model, an immune algorithm is presented to find a set of activity priorities that are combined with dispatching rules to allocate resources. Activity priorities are represented by antibodies and evaluated by simulation runs on the workflow model. The proposed approach is applied to several production scheduling instances, and results are compared with other approaches. Experiments show that the result from the proposed approach is substantially better than those obtained from other approaches. It is demonstrated that our approach can effectively reduce production tardiness and improve efficiency.
机译:卷烟生产计划对于提高生产效率和减少供应延迟至关重要。为了提高生产效率,提出了一种结合免疫算法的工作流模型。首先,将问题表述为混合整数二次约束规划模型。之后,将问题转化为工作流资源分配之一。基于此模型,提出了一种免疫算法来查找一组活动优先级,这些活动优先级与调度规则结合以分配资源。活性优先级由抗体表示,并通过在工作流程模型上进行的仿真评估。将该方法应用于多个生产调度实例,并将结果与​​其他方法进行比较。实验表明,所提方法的结果明显优于其他方法。事实证明,我们的方法可以有效地减少生产延迟,提高效率。

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