Optimal ordering policies for periodic-review systems with a refined intra-cycle time scale

Chiang, Chi

doi:10.1016/j.ejor.2005.11.026

Cited by 18 publications

(8 citation statements)

References 6 publications

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“…In staggered systems, and in some periodic review systems, it is common to ignore cycle stock and to apply inventory costs to the inventory level at the end of each replenishment cycle, just before new receipts arrive. This can be compared with the non-staggered models in Silver and Robb (2008) and Chiang (2007), which permit inventory inspections (with associated costs) between two subsequent receipts.…”

Section: Literature Reviewmentioning

confidence: 99%

Inventory performance under staggered deliveries and autocorrelated demand

Hedenstierna

Disney

2016

European Journal of Operational Research

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Production plans often span a whole week or month, even when independent production lots are completed every day and service performance is tallied daily. Such policies are said to use staggered deliveries, meaning that the production rate for multiple days are determined at a single point in time. Assuming autocorrelated demand, and linear inventory holding and backlog costs, we identify the optimal replenishment policy for order cycles of length P. With the addition of a once-per-cycle audit cost, we optimize the order cycle length P * via an inverse-function approach. In addition, we characterize periodic inventory costs, availability, and fill rate. As a consequence of staggering deliveries, the inventory level becomes cyclically heteroskedastic. This manifests itself as ripples in the expected cost and service levels. Nevertheless, the cost-optimal replenishment policy achieves a constant availability by using time-varying safety stocks; this is not the case with suboptimal constant safety stock policies, where the availability fluctuates over the cycle.

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Section: Literature Reviewmentioning

confidence: 99%

Inventory performance under staggered deliveries and autocorrelated demand

Hedenstierna

Disney

2016

European Journal of Operational Research

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“…Based on numerical examples it is shown that such policies are not optimal for models with a cost objective in a lost-sales setting (see, eg, Hill, 1999;Hill and Johansen, 2006). Fractional lead times in a lost-sales inventory system with a cost objective are considered by Chiang (2006Chiang ( , 2007. For more information on the cost model, we refer to Hill and Johansen (2006), Bijvank and Johansen (2009), Bijvank and Vis (2011) and the references therein.…”

Section: Literature Overviewmentioning

confidence: 99%

Inventory control for point-of-use locations in hospitals

Bijvank

Vis

2012

Journal of the Operational Research Society

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Most inventory management systems at hospital departments are characterised by lost sales, periodic reviews with short lead times, and limited storage capacity. We develop two types of exact models that deal with all these characteristics. In a capacity model, the service level is maximised subject to a capacity restriction, and in a service model the required capacity is minimised subject to a service level restriction. We also formulate approximation models applicable for any lost-sales inventory system (cost objective, no lead time restrictions etc). For the capacity model, we develop a simple inventory rule to set the reorder levels and order quantities. Numerical results for this inventory rule show an average deviation of 1% from the optimal service levels. We also embed the single-item models in a multi-item system. Furthermore, we compare the performance of fixed order size replenishment policies and (R, s, S) policies.

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“…However, this has several shortcomings for one or few weeks long reorder intervals. In order to remedy these shortcomings, Chiang (2006Chiang ( , 2007 introduces different dynamic programming models for both backorder and lost-sales cases in which holding and shortage costs are computed based on the ending inventory of each period that composes the reorder interval. For the lost-sales case, he assumes that lead time is less than or equal to the length of reorder intervals.…”

Section: Related Literaturementioning

confidence: 99%

Optimising reorder intervals and order-up-to levels in guaranteed service supply chains

Eruguz¹,

Jemaı̈

Şahin

2013

International Journal of Production Research

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We consider the problem of determining the optimal reorder intervals R and order-up-to levels S in a multi-echelon supply chain system where all echelons are assumed to have fixed ordering costs and to operate with a (R, S) policy with stationary nested power-of-two reorder intervals. By using the guaranteed service approach to model the multi-echelon system facing a stochastic demand, we formulate the problem as a deterministic optimisation model in order to simultaneously determine the optimal R and S parameters as well as the guaranteed service times. The model is a non-linear integer programming (NLIP) problem with a non-convex and non-concave objective function including rational and square root terms. Then, we propose a sequential optimisation procedure (SOP) to obtain near-optimal solutions with reasonable computational time. The numerical study demonstrates that for a general acyclic multi-echelon system with randomly generated parameters, the SOP is able to obtain near-optimal solutions of about 0.46% optimality gap in average in a few seconds. Moreover, we propose an improved direct approach using a global optimiser, bounding the decision variables in the NLIP model and considering the SOP solution as an initial solution. Numerical examples illustrate that this reduces significantly the computational time.Keywords: inventory control; multi-echelon system; guaranteed service model; power-of-two policies IntroductionMany real-world supply chains are complex multi-echelon systems consisting of suppliers, manufacturers, wholesalers and retailers that have geographically dispersed facilities. One challenge these supply chains face is the efficient management of inventory when demand is uncertain, operating costs are important and customer service requirements are high. This requires specifying the inventory policy at different echelons so that to minimise the total cost of the whole multi-echelon system subject to customer service levels (Simchi-Levi and Zhao 2012). The guaranteed service model (GSM) which is among the relevant approaches that can be used in multi-echelon inventory systems has gained interest in recent years. In particular, this model enabled to realise important benefits in practice in general multi-echelon systems which combine distribution and assembly systems (see e.g. Billington et al. 2004;Farasyn et al. 2011).In this paper, we build on the power-of-two (PO2) and the GSM research to find a reasonable solution to the problem of simultaneously optimising the reorder intervals and order-up-to levels for general multi-echelon systems facing stochastic demand. Finding an optimal policy for this problem would be extremely difficult. Indeed, the optimal policy is not known even for two-echelon distribution systems with deterministic demand (Snyder and Shen 2011). In order to deal with demand variations, we use the original assumptions of the GSM that are the guaranteed service time and the bounded demand assumptions. Besides, we assume that each stage of the supply chain operates with a peri...

show abstract

Optimal ordering policies for periodic-review systems with a refined intra-cycle time scale

Cited by 18 publications

References 6 publications

Inventory performance under staggered deliveries and autocorrelated demand

Inventory performance under staggered deliveries and autocorrelated demand

Inventory control for point-of-use locations in hospitals

Optimising reorder intervals and order-up-to levels in guaranteed service supply chains

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