چکیده:
Modern retail supply chains are more and more exposed to risks and uncertainties. Supply risks such as the uncertainty of the supplier fill rate (SFR) directly affect the performance of a retail supply chain. The purpose of this paper is to investigate the supply uncertainty, where the order size and the supply lead-time are considered as decision variables. We aim at developing a more realistic approach to predicting the SFR. Reviewing the relevant literature was the first step taken. We pointed out that while the scientific research on supply risk is growing, the literature lacks an accurate support tool that can predict the SFR. Then, a case study was conducted in order to have a comprehensive view of the real context of SFR parameters. Accordingly, we propose a new approach to predicting the SFR using the bivariate normal distribution. We illustrate the proposed approach using a real case study in Tunisia.
خلاصه ماشینی:
The supplier fill rate (SFR) directly affects the performance of a retail supply chain (Ehrenthal and Stölzle 2013).
As shown in Figure 2, to control the WC inventory, the manager uses a replenishment policy similar to the standard periodic review base stock policy (T, S) with random demand and random lead-time.
As shown in Table 1, supply risk and uncertainty is often modeled using random yields, random SFR or supply service level (SSL) and supply lead-time variability.
In this study, they investigate the continuous review inventory model with shortages including the case where the quantity received is uncertain, in which the lead time, lost sales rate, and order processing cost are decision variables.
There is a rich body of literature on supplier-retailer inventory models with uncertain supply lead-time and the effect of supply uncertainty on supply chain performance (Schmitt et al.
, 2010) (Gupta and Cooper, 2005), (Yang et al.
2012), (Tang and Kouvelis 2011), (Wang et al.
We do not merely assume the supplier lead-time to be a random exogenous variable, but we include the impact of the order size decision on the supply lead-time and we use the result to predict the SFR.
Moreover, the proposed approach can help the decision maker to estimate the SFR based on a bivariate distribution taking into account the order size variability and lead time uncertainty.
Continuous review inventory model with controllable lead time, lost sales rate and order processing cost when the received quantity is uncertain, Journal of Manufacturing Systems, Vol. 34, pp.