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Integrated Production and Imperfect Preventive Maintenance Planning: An Effective MILP-based Relax-and-Fix/Fix-and-Optimize Method

机译:综合生产和不完美预防性维护规划:基于摩尔普的静态宽松和修复/修复和优化方法

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This paper investigates the integrated production and imperfect preventive maintenance planning problem. The main objective is to determine an optimal combined production and maintenance strategy that concurrently minimizes production as well as maintenance costs during a given finite planning horizon. To enhance the quality of the solution and improve the computational time, we reconsider the reformulation of the problem proposed in (Aghezzaf et al., 2016) and then solved it with an effective MILP-based Relax-and-Fix/Fix-and-Optimize method (RFFO). The results of this Relax-and-Fix/Fix-and-Optimize technique were also compared to those obtained by a Dantzig-Wolfe Decomposition (DWD) technique applied to this same reformulation of the problem. The results of this analysis show that the RFFO technique provides quite good solutions to the test problems with a noticeable improvement in computational time. DWD on the other hand exhibits a good improvement in terms of computational times, however, the quality of the solution still requires some more improvements.
机译:本文调查了综合生产和不完美预防性维护计划问题。主要目的是确定在给定的有限规划地平线期间同时最大限度地减少生产以及维护成本的最佳组合生产和维护策略。为了提高解决方案的质量并改善计算时间,我们重新考虑了(Aghezzaf等,2016)所提出的问题的重新考虑,然后用一个有效的基于MILP的放松和修复/修复 - 优化方法(RFFO)。还将这种放松和修复/修复和优化技术的结果与通过应用于该问题的同样重构的Dantzig-Wolfe分解(DWD)技术获得的结果。该分析的结果表明,RFFO技术为测试问题提供了非常好的解决方案,在计算时间内具有明显的改善。另一方面,DWD在计算时间方面表现出良好的改进,然而,解决方案的质量仍需要更多的改进。

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