Optimal procurement policies under price-dependent demand

Polatoglu, Hakan; Şahin, İzzet

doi:10.1016/s0925-5273(98)00240-0

Cited by 71 publications

(33 citation statements)

References 18 publications

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“…This lemma, of course, is consistent with the observation made by Polatoglu and Sahin (2000) for the lost sales model.…”

Section: Lemma 4 There Exists An Instance Of Problem (2) With Multipsupporting

confidence: 89%

“…Thus, if an order is placed, it is always to raise the inventory level to S t . Note that in the lost sales case, there might exist multiple order-up-to levels, as demonstrated by Polatoglu and Sahin (2000). Thus, the optimal policy for the backorder model, s S A p proven in this paper, is different than the structure of the policy for the lost sales model.…”

Section: A T = I T ∩ S T S T + S T /2mentioning

confidence: 84%

“…Thomas goes on to say: "If all prices in an interval are under consideration, it is conjectured that an s S p policy is optimal under fairly general conditions" (Thomas 1974, p. 517). Polatoglu and Sahin (2000) also consider a model similar to ours. However, unlike in our model, they assume unsatisfied demand is lost.…”

Section: Introductionmentioning

confidence: 99%

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Coordinating Inventory Control and Pricing Strategies with Random Demand and Fixed Ordering Cost: The Finite Horizon Case

Chen

Simchi‐Levi

2004

Operations Research

382

237

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We analyze a finite horizon, single product, periodic review model in which pricing and production/inventory decisions are made simultaneously. Demands in different periods are random variables that are independent of each other and their distributions depend on the product price. Pricing and ordering decisions are made at the beginning of each period and all shortages are backlogged. Ordering cost includes both a fixed cost and a variable cost proportional to the amount ordered. The objective is to find an inventory policy and a pricing strategy maximizing expected profit over the finite horizon. We show that when the demand model is additive, the profit-to-go functions are k-concave and hence an s S p policy is optimal. In such a policy, the period inventory is managed based on the classical s S policy and price is determined based on the inventory position at the beginning of each period. For more general demand functions, i.e., multiplicative plus additive functions, we demonstrate that the profit-to-go function is not necessarily k-concave and an s S p policy is not necessarily optimal. We introduce a new concept, the symmetric k-concave functions, and apply it to provide a characterization of the optimal policy.

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“…This lemma, of course, is consistent with the observation made by Polatoglu and Sahin (2000) for the lost sales model.…”

Section: Lemma 4 There Exists An Instance Of Problem (2) With Multipsupporting

confidence: 89%

Section: A T = I T ∩ S T S T + S T /2mentioning

confidence: 84%

See 1 more Smart Citation

Coordinating Inventory Control and Pricing Strategies with Random Demand and Fixed Ordering Cost: The Finite Horizon Case

Chen

Simchi‐Levi

2004

Operations Research

382

237

View full text Add to dashboard Cite

show abstract

“…When unsatisfied demands are assumed to be lost, Polatoglu and Sahin (2000) characterize the form of the optimal replenishment policy under a general price-demand relationship and provide a sufficient condition for it to be of the (s, S)-type. For a finite horizon system, Chen, Ray and Song (2003) and Huh and Janakiraman (2005) have proved the optimality of an (s, S, p) policy under assumptions of stationary parameters and a salvage value that is equal to the unit purchasing cost.…”

Section: Introductionmentioning

confidence: 99%

Joint pricing and inventory control with a Markovian demand model

Yin

Rajaram

2007

European Journal of Operational Research

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We consider the joint pricing and inventory control problem for a single product with a finite horizon and periodic review. The demand distribution in each period is determined by an exogenous Markov chain. Pricing and ordering decisions are made at the beginning of each period and all shortages are backlogged. The surplus costs as well as fixed and variable costs are state dependent. We show the existence of an optimal (s, S, p)-type feedback policy for the additive demand model. We extend the model to the case of emergency orders and also incorporate capacity and service level constraints. We compute the optimal policy for a class of Markovian demand and illustrate the benefits of dynamic pricing over fixed pricing strategies through numerical examples. The results indicate that it is more beneficial to implement the dynamic pricing strategy in a Markovian demand environment with a high fixed ordering cost or with high demand uncertainty.

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“…A related paper is the one by Polatoglu and Sahin [121]. They consider a model similar to the one by Thomas but assume that the backorder cost is a non-decreasing function of price.…”

Section: 22mentioning

confidence: 99%