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When is it feasible to model low discrete demand by a normal distribution?

机译:什么时候可以通过正态分布对低离散需求建模?

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Inventory control systems used in practice are quite often modeling the lead-time demand by a normal distribution. This may result in considerable errors when the real demand is low and discrete. For such demand, it is usually better to use a discrete demand distribution. However, this will increase the computational effort. A natural question is under what circumstances a normal approximation is feasible. This paper analyzes this question in a numerical study. Our study indicates that a normal approximation works reasonably well when the average lead-time demand is something like 10 or higher and the coefficient of variation is bounded by something like 2. The normal approximation works better for a high backorder cost or, equivalently, a high service level.
机译:在实践中使用的库存控制系统通常通过正态分布对交货时间需求进行建模。当实际需求低且离散时,这可能会导致相当大的错误。对于此类需求,通常最好使用离散需求分配。但是,这将增加计算量。一个自然的问题是在什么情况下可以正常近似。本文在数值研究中分析了这个问题。我们的研究表明,当平均提前期需求大约为10或更高且变异系数受2左右为界时,正常近似法可以很好地工作。对于较高的滞销成本或等效地,正常近似法可以更好地工作。服务水平高。

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