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Fuzzy-metaheuristic methods to solve a hybrid flow shop scheduling problem with pre-assignment

机译:带有预分配的混合流水车间调度问题的模糊磁滞方法

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This paper deals with a particular version of the hybrid flow shop scheduling problem inspired from a real application in the automotive industry. Specific constraints such as pre-assigned jobs, non-identical parallel machines and non-compatibility between certain jobs and machines are considered in order to minimise the total tardiness time. A mixed-integer programming model that incorporates these aspects is developed and solved using ILOG Cplex software. Thus, because of the computation time constraint, we propose approximate resolution methods based on genetic and particle swarm optimisation algorithms coupled or not with fuzzy logic control. The effectiveness of these methods is investigated via computational experiments based on theoretical and real case instances. The obtained results show that fuzzy logic control improves the performances of both genetic and particle swarm optimisation algorithms significantly.
机译:本文探讨了混合流水车间调度问题的特定版本,该问题受汽车行业实际应用的启发。为了最小化总拖延时间,考虑了特定的约束条件,例如预先分配的作业,不相同的并行计算机以及某些作业和计算机之间的不兼容。使用ILOG Cplex软件开发并解决了包含这些方面的混合整数编程模型。因此,由于计算时间的限制,我们提出了基于遗传和粒子群优化算法或不结合模糊逻辑控制的近似解析方法。通过基于理论和实际案例的计算实验来研究这些方法的有效性。所得结果表明,模糊逻辑控制显着提高了遗传和粒子群优化算法的性能。

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