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Multi-objective open shop scheduling by considering human error and preventive maintenance

机译：考虑人为错误和预防性维护的多目标开放车间调度

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This study presents an open shop scheduling model by considering human error and preventive maintenance. The proposed mathematical model takes into account conflicting objective functions including makespan, human error and machine availability. In order to find the optimum scheduling, human error, maintenance and production factors are considered, simultaneously. Human error is measured by Human Error Assessment and Reduction Technique (HEART). Three metaheuristic methods including non-dominated sorting genetic algorithm-II (NSGA-II), multi-objective particle swarm optimization (MOPSO) and strength Pareto evolutionary algorithm II (SPEA-II) are developed to find near-optimal solution. The Taguchi method is applied by adjusting parameters of metaheuristic algorithms. Several illustrative examples and a real case study (auto spare parts manufacturer) are applied to show the applicability of the multi-objective mixed integer nonlinear programming model. The proposed approach of this study may be used for similar open shop problems with minor modifications. (C) 2018 Elsevier Inc. All rights reserved.
机译：这项研究通过考虑人为错误和预防性维护提出了一种开放式车间调度模型。所提出的数学模型考虑了相互冲突的目标函数，包括制造期，人为错误和机器可用性。为了找到最佳计划，同时考虑了人为错误，维护和生产因素。人为错误通过人为错误评估和减少技术（HEART）进行测量。开发了三种元启发式方法，包括非支配排序遗传算法-II（NSGA-II），多目标粒子群优化（MOPSO）和强度帕累托进化算法II（SPEA-II），以寻找接近最优的解决方案。 Taguchi方法是通过调整元启发式算法的参数来应用的。应用几个说明性示例和一个实际案例研究（汽车零部件制造商）来显示多目标混合整数非线性规划模型的适用性。这项研究的建议方法可用于类似的开放式商店问题，但需进行少量修改。 （C）2018 Elsevier Inc.保留所有权利。

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