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A new mathematical model for single machine batch scheduling problem for minimizing maximum lateness with deteriorating jobs

机译:用于单机批处理调度问题的新数学模型,可最大程度地减少因工作恶化而导致的最大延迟

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This paper presents a mathematical model for the problem of minimizing the maximum lateness on a single machine when the deteriorated jobs are delivered to each customer in various size batches. In reality, this issue may happen within a supply chain in which delivering goods to customers entails cost. Under such situation, keeping completed jobs to deliver in batches may result in reducing delivery costs. In literature review of batch scheduling, minimizing the maximum lateness is known as NP-Hard problem; therefore the present issue aiming at minimizing the costs of delivering, in addition to the aforementioned objective function, remains an NP-Hard problem. In order to solve the proposed model, a Simulation annealing meta-heuristic is used, where the parameters are calibrated by Taguchi approach and the results are compared to the global optimal values generated by Lingo 10 software. Furthermore, in order to check the efficiency of proposed method to solve larger scales of problem, a lower bound is generated. The results are also analyzed based on the effective factors of the problem. Computational study validates the efficiency and the accuracy of the presented model.
机译:本文提出了一个数学模型,用于解决在将各种尺寸的批次的劣质工作交付给每个客户时,将一台机器上的最大延迟最小化的问题。实际上,此问题可能发生在供应链中,向客户交付商品会带来成本。在这种情况下,保留已完成的作业以分批交付可能会降低交付成本。在批处理计划的文献回顾中,最大程度地减少最大延迟被称为NP-Hard问题。因此,除了上述目标功能之外,旨在最小化交付成本的当前问题仍然是NP-Hard问题。为了解决所提出的模型,使用了模拟退火元启发式算法,其中通过Taguchi方法对参数进行校准,并将结果与​​Lingo 10软件生成的全局最优值进行比较。此外,为了检验所提出的解决较大规模问题的方法的效率,产生了下界。还基于问题的有效因素来分析结果。计算研究验证了所提出模型的效率和准确性。

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