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Augmented epsilon-constraint method in multi-objective flowshop problem with past sequence set-up times and a modified learning effect

机译:具有过去序列建立时间和改进学习效果的多目标流水车间问题的增强ε约束方法

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摘要

This article addresses a general tri-objective non-permutation flowshop problem to minimise the makespan, the sum of flow time and maximum tardiness simultaneously. In order to enhance the applicability of the model, some practical assumptions are included. These are release dates, past sequence-dependent set-up times, a truncated generalisation of Dejong's learning effect and predetermined machine availability constraints. First, the problem is formulated as a mixed-integer linear programming model. Second, the true Pareto front is achieved with augmented epsilon-constraint method for small-sized problems. Third, due to the high complexity of the model and the impractical computational times of larger instances, a heuristic algorithm based on the epsilon-constraint method is also proposed. Finally, the algorithms are tested to gauge their effectiveness, and the results are compared with other methods.
机译:本文介绍了一个通用的三目标非置换流水车间问题,以同时最小化制造期,流动时间之和和最大延误。为了增强模型的适用性,包括了一些实际的假设。这些是发行日期,过去依赖于序列的设置时间,对Dejong学习效果的截断概括和预定的机器可用性约束。首先,将问题表述为混合整数线性规划模型。其次,通过增强的ε约束方法来解决小问题,从而获得真正的帕累托前沿。第三,由于模型的高复杂度和较大实例的不实际计算时间,还提出了一种基于ε约束方法的启发式算法。最后,对算法进行测试以评估其有效性,并将结果与​​其他方法进行比较。

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