On computing optimal (Q,r) replenishment policies under quantity discounts

Katehakis, Michael N.; Smit, Laurens C.

doi:10.1007/s10479-012-1071-z

Cited by 30 publications

(9 citation statements)

References 7 publications

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“…Similar studies of endogenously determined response times fall under the category of time-based competition [see e.g., 48,69]. For other related work, we refer to [39,44,53,54], and references therein.…”

Section: Literature Reviewmentioning

confidence: 99%

Dynamic pricing in a dual‐market environment

Chen

Fleischhacker²,

Katehakis³

2015

Naval Research Logistics

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This paper is concerned with the determination of pricing strategies for a firm that in each period of a finite horizon receives replenishment quantities of a single product which it sells in two markets, e.g., a long-distance market and an on-site market. The key difference between the two markets is that the long-distance market provides for a one period delay in demand fulfillment.In contrast, on-site orders must be filled immediately as the customer is at the physical on-site location. We model the demands in consecutive periods as independent random variables and their distributions depend on the item's price in accordance with two general stochastic demand functions: additive or multiplicative. The firm uses a single pool of inventory to fulfill demands from both markets. We investigate properties of the structure of the dynamic pricing strategy that maximizes the total expected discounted profit over the finite time horizon, under fixed or controlled replenishment conditions. Further, we provide conditions under which one market may be the preferred outlet to sale over the other.

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Section: Literature Reviewmentioning

confidence: 99%

Dynamic pricing in a dual‐market environment

Chen

Fleischhacker²,

Katehakis³

2015

Naval Research Logistics

Self Cite

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“…This work uses a multiobjective time and cost optimization that considers total inventory turnover time and inventory cost. Katehakis and Smit (2012) studies the continuous review (Q, r) inventory policy and shows that the policy is optimal for quantity discounts. Lee and Behnezhad (2015) further shows that an order-up-to policy is optimal under a general demand distribution for the same incremental quantity discount model for a multi-period and infinite horizon setting.…”

Section: Inventory and Supply Managementmentioning

confidence: 99%

A Salt Inventory Management Strategy for Winter Maintenance

Ciarallo

Niranjan

Brown³

2015

OSCM: An Int. Journal

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Expenditures for winter maintenance materials total nearly $20 million annually in a mid-western USA state. During an average winter the State Department of Transportation (DOT) uses approximately 666,000 tons of rock salt and has the capacity to store roughly 617,000 tons of material at various locations. Each year, each county in this Mid-western state establishes a contract through DOT with a salt vendor before the winter season and that vendor supplies all garages in the county for the entire season. In order to develop a systematic salt inventory management strategy that achieves the statewide goals for safety, ordering guidelines for each county that specify when to order and how much to order based on an (R, S)-inventory guideline is developed. These guidelines take into account the history of usage and deliveries in a county, as well as the monthly variation in usage. The inventory guidelines developed for the different areas of the state are based on a weather regression model for the major cities/counties in the state relating usage to weather. The guidelines were tested and refined using a computer simulation methodology. The resulting guidelines are compared to the state's current DOT guidelines for inventory, as well as compared to the county storage capacities to develop recommendations.

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“…In Axsäter (2003b) an approximate method is developed that uses information about the residual leadtimes of the items in the system. Other relevant literature concerning batch-ordering policies include, e.g., Axsäter (2000) and Katehakis and Smit (2012).…”

Section: Introduction and Literature Reviewmentioning

confidence: 99%

Quantifying sustainable control of inventory systems with non-linear backorder costs

Johansson

Olsson

2017

Ann Oper Res

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Traditionally, when optimizing base-stock levels in spare parts inventory systems, it is common to base the decisions either on a linear shortage cost or on a certain target fill rate. However, in many practical settings the shortage cost is a non-linear function of the customer waiting time. In particular, there may exist contracts between the spare parts provider and the customer, where the provider is obliged to pay a fixed penalty fee if the spare part is not delivered within a certain time window. We consider a two-echelon inventory system with one central warehouse and multiple local sites. Focusing on spare parts products, we assume continuous review base stock policies. We first consider a fixed backorder cost whenever a customer's time in backorder exceeds a prescribed time limit, second a general non-linear backorder cost as a function of the customer waiting time, and third a time window service constraint. We show from a sustainability perspective how our model may be used for evaluating the expected CO 2 emissions associated with not satisfying the customer demands on time. Finally, we generalize some known inventory models by deriving exact closed form expressions of inventory level distributions.

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On computing optimal (Q,r) replenishment policies under quantity discounts

Cited by 30 publications

References 7 publications

Dynamic pricing in a dual‐market environment

Dynamic pricing in a dual‐market environment

A Salt Inventory Management Strategy for Winter Maintenance

Quantifying sustainable control of inventory systems with non-linear backorder costs

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