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首页> 外文期刊>International Journal of Production Research >A hybrid computer simulation-artificial neural network algorithm for optimisation of dispatching rule selection in stochastic job shop scheduling problems
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A hybrid computer simulation-artificial neural network algorithm for optimisation of dispatching rule selection in stochastic job shop scheduling problems

机译：随机作业车间调度问题中优化调度规则选择的混合计算机仿真-人工神经网络算法

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摘要

Industrial systems are constantly subject to random events with inevitable uncertainties in production factors, especially in processing times. Due to this stochastic nature, selecting appropriate dispatching rules has become a major issue in practical problems. However, previous research implies that using one dispatching rule does not necessarily yield an optimal schedule. Therefore, a new algorithm is proposed based on computer simulation and artificial neural networks (ANNs) to select the optimal dispatching rule for each machine from a set of rules in order to minimise the makespan in stochastic job shop scheduling problems (SJSSPs). The algorithm contributes to the previous work on job shop scheduling in three significant ways: (1) to the best of our knowledge it is the first time that an approach based on computer simulation and ANNs is proposed to select dispatching rules; (2) non-identical dispatching rules are considered for machines under stochastic environment; and (3) the algorithm is capable of finding the optimal solution of SJSSPs since it evaluates all possible solutions. The performance of the proposed algorithm is compared with computer simulation methods by replicating comprehensive simulation experiments. Extensive computational results for job shops with five and six machines indicate the superiority of the new algorithm compared to previous studies in the literature.
机译：工业系统经常受到随机事件的影响，在生产因素（尤其是加工时间）中不可避免地存在不确定性。由于这种随机性，选择合适的调度规则已成为实际问题中的主要问题。但是，先前的研究表明，使用一种调度规则不一定能产生最佳调度。因此，提出了一种基于计算机仿真和人工神经网络（ANN）的新算法，以从一组规则中为每台机器选择最佳调度规则，以最大程度地减少随机作业车间调度问题（SJSSP）的工期。该算法以三种重要方式为先前的车间调度工作做出了贡献：（1）据我们所知，这是首次提出一种基于计算机仿真和ANN的方法来选择调度规则； （2）随机环境下的机器考虑不同的调度规则； （3）该算法能够评估SJSSP的最优解，因为它可以评估所有可能的解。通过复制全面的仿真实验，将该算法的性能与计算机仿真方法进行了比较。具有五台和六台机器的车间的大量计算结果表明，与文献中的先前研究相比，该新算法具有优越性。

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