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Optimization of reliability based model for production inventory system

机译:基于可靠性的生产库存系统模型优化

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摘要

Traditional research studies on the Economic Production Quantity (EPQ) model propose that produced items have perfect quality. However, in real production systems the quality of the products depends on the production process reliability. EPQ models that consider reliability and the effect of imperfect items are much more complex, and in turn the objective function becomes much more complicated. It is challenging to solve this type of model analytically, and it is also time consuming. Hence, it is necessary to utilize non-traditional solution techniques, such as numerical methods and heuristic search algorithms, for solving this type of model. In this paper, the optimal solution of the EPQ based reliability model are obtained by analytical solution, a Generalized Reduced Gradient (GRG) algorithm, an Evolutionary Algorithm (EA), a Monte Carlo non-deterministic method and the LINGO™ commercial solver. The methodology of this work has been clearly presented, and the computational results are compared and discussed.The computational results show that the GRG, EA, and Monte Carlo methods result in feasible and similar solutions, while the analytical solution is not valid for the model studied. The model can be extended to solve more complicated inventory models considering rework, shortage and multiple products.
机译:传统的关于经济生产数量(EPQ)模型的研究表明,生产的物品具有完美的质量。但是,在实际的生产系统中,产品的质量取决于生产过程的可靠性。考虑可靠性和不完善项目影响的EPQ模型要复杂得多,目标函数也要复杂得多。通过解析来解决这种类型的模型具有挑战性,并且也很耗时。因此,有必要利用非传统的求解技术,例如数值方法和启发式搜索算法来求解这种类型的模型。本文通过分析解决方案,广义降梯度(GRG)算法,进化算法(EA),蒙特卡洛非确定性方法和LINGO™商业求解器来获得基于EPQ的可靠性模型的最佳解决方案。清楚地介绍了这项工作的方法,并对计算结果进行了比较和讨论。计算结果表明,GRG,EA和Monte Carlo方法可得出可行且相似的解,而解析解对该模型无效研究。考虑到返工,短缺和多种产品,可以扩展该模型以解决更复杂的库存模型。

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