Dynamic scheduling in flexible job shop systems by considering simultaneously efficiency and stability
Dynamic scheduling in flexible job shop systems by considering simultaneously efficiency and stability
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DOI：
10.1016/j.cirpj.2009.10.001
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发表时间：
2010-01-01
影响因子：
4.8
通讯作者：
Fallahi, Alireza
中科院分区：
文献类型：
--
作者：
Fattahi, Parviz;Fallahi, Alireza
柔性作业车间调度问题在生产管理和组合优化等领域具有重要意义。然而，在中等规模和实际规模的问题中，由于计算的复杂性，用传统的优化方法很难得到该问题的最优解。本文研究了柔性作业车间的动态调度问题。这种动态状态加剧了这一问题的复杂性。尽管如此，仍有许多行业处于动态状态。考虑了两个目标，以平衡调度的效率和稳定性。建立了所考虑问题的多目标数学模型。由于该问题是NP-Hard问题，提出了一种基于遗传算法的元启发式算法。通过数值实验对该算法的性能和效率进行了评估。实验结果表明，该算法能够获得小规模问题的最优解和中等规模问题的近最优解。(C)2009年CIRP。
Scheduling for the flexible job shop is very important in the fields of production management and combinatorial optimization. However, it is quite difficult to achieve an optimal solution to this problem in medium and actual size problems with traditional optimization approaches owing to the high computational complexity. In this paper, dynamic scheduling in flexible job shop is considered. The dynamic status intensifies the complexity of this problem. Nevertheless, there are many industries which have a dynamic status. Two objectives are considered to make a balance between efficiency and stability of the schedules. A multi-objective mathematical model for the considered problem is developed. Since the problemiswell known as NP-hard, a meta-heuristic algorithm based on the genetic algorithm is developed. Numerical experiments are used to evaluate the performance and efficiency of the proposed algorithm. The experimental results show that the proposed algorithm is capable to achieve the optimal solutions for the small size problems and near optimal solutions for the mediumsize problems. (C) 2009 CIRP.