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Preventive maintenance effect on the aggregate production planning model with tow-phase production systems: modeling and solution methods

机译:两阶段生产系统对总体生产计划模型的预防性维护影响:建模和解决方法

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This paper develops two mixed integer linear programming (MILP) models for an integrated aggregate production planning (APP) system with return products, breakdowns and preventive maintenance (PM). The goal is to minimize the cost of production with regard to PM costs, breakdowns, the number of laborers and inventory levels and downtimes. Due to NP-hard class of APP, we implement a harmony search (HS) algorithm and vibration damping optimization (VDO) algorithm for solving these models. Next, the Taguchi method is conducted to calibrate the parameter of the metaheuristics and select the optimal levels of factors influencing the algorithm’s performance. Computational results tested on a set of randomly generated instances show the efficiency of the vibration damping optimization algorithm against the harmony search algorithm. We find VDO algorithm to obtain best quality solutions for APP with breakdowns and PM, which could be efficient for large scale problems. Finally, the computational results show that the objective function values obtained by APP with PM are better than APP with breakdown results
机译:本文针对带有退货,故障和预防性维护(PM)的集成总生产计划(APP)系统开发了两个混合整数线性规划(MILP)模型。目标是在PM成本,故障,劳动力数量以及库存水平和停机时间方面将生产成本降至最低。由于APP的NP-hard类,我们实现了和谐搜索(HS)算法和振动阻尼优化(VDO)算法来求解这些模型。接下来,使用Taguchi方法校准元启发法的参数,并选择影响算法性能的最佳因素水平。在一组随机生成的实例上测试的计算结果表明,减振优化算法相对于和声搜索算法的效率更高。我们发现VDO算法可为带有故障和PM的APP获得最佳质量的解决方案,这对于解决大规模问题可能是有效的。最后,计算结果表明,带有PM的APP获得的目标函数值要比具有细分结果的APP更好。

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