Abstract

Due to the uncertainty of market economy as well as fluctuation of customer’s demand, appropriate modelling of an inventory problem is a challenging task to the researchers/OR practitioners. In order to overcome this type of challenging situation, in this article, using the parametric approach of interval a non-deterministic inventory model for deteriorating items with partially backlogged shortages and interval-valued deterioration rate has been developed. Here, the demand rate is considered to be interval-valued and dependent upon the selling price which is also interval-valued. Also, all the parameters (like ordering cost, holding cost, etc.) except the backlogging parameter have been considered as interval-valued. The corresponding problem has been formulated as a maximization problem with an interval-valued objective. Then, to solve the said problem, we have used different variants of the QPSO algorithm with interval fitness using interval ranking. Then, the computational results have been illustrated with the help of three numerical examples. Finally, the sensitivity of the solution has been analysed with the changes in the values of different parameters associated with the model and a fruitful conclusion has been drawn.

中文翻译：

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区间微分方程参数化方法在带有价格依赖需求的变质物品库存模型中的应用

摘要

由于市场经济的不确定性以及客户需求的波动，对库存问题进行适当的建模对于研究人员或从业人员而言是一项艰巨的任务。为了克服这种挑战性的情况，在本文中，使用区间的参数化方法，开发了一种不确定的库存模型，用于恶化带有部分积压的短缺和区间值恶化率的物品的恶化。在此，需求率被认为是区间值，并取决于也是区间值的售价。另外，除积压参数以外的所有参数（如订购成本，保存成本等）都被视为间隔值。相应的问题已被公式化为具有区间值目标的最大化问题。然后，为了解决上述问题，我们使用了QPSO算法的不同变体，并采用了区间排序的区间适应性。然后，借助三个数值示例说明了计算结果。最后，通过与模型相关的不同参数值的变化来分析解决方案的敏感性，并得出了富有成果的结论。