The single-period inventory problem: Extension to random yield from the perspective of the supply chain

A special form of the single-period inventory problem (newsvendor problem) with a known demand and stochastic supply (yield) is studied. A general analytic solution for two types of yield risks, additive and multiplicative, is described. Numerical examples demonstrate the solutions for special cases of uniform distribution yield risks. An analysis of a two-tier supply chain of customer and producer reveals that the customer may find it optimal to order more than is needed, since a larger order increases the producer's optimal production quantity.     

On service degrade at a discount: Capacity, demand pooling, and optimal discounting

In this paper we study the capacity investment decisions and operational strategies of a firm providing two-class services facing uncertain demands. The capacity decisions of the resources are made before demands are observed. Each service can be implemented by its corresponding resource. Should a mismatch between the capacity and the actual demand for the services arise, the low-class resource can be used as a substitute for the high-class service. We introduce an operational strategy called degrade-at-a-discount, where a price discount is offered to motivate customers to accept a lower class service when their original choice is out of capacity. By formulating the problem as a one-period, two-stage stochastic problem, we analyze how to set up the optimal capacity and the optimal discount. We also conduct a comprehensive numerical study to show the benefits of the degrade-at-a-discount strategy.     

Risk tolerance and a retailer's pricing and ordering policies within a newsvendor framework

This paper evaluates the pricing and ordering policies of a retailer, facing a price-dependent stochastic demand, within a newsvendor framework, under different degrees of risk tolerance and under a variety of optimizing objectives. These are (i) maximizing expected profit, for a retailer who may be risk-seeker, risk-averse or risk neutral; (ii) deriving a maximin strategy of maximizing a minimum guaranteed profit and (iii) modeling the probability of exceeding a target profit, as a constraint or as an objective. Some analytical properties and numerical examples illustrate the main features of the models and provide some comparative policy analysis across the model.     

The value of VMI beyond information sharing in a single supplier multiple retailers supply chain under a non-stationary (Rn,Sn) policy

This study aims to determine the value of vendor-managed inventory (VMI) over independent decision making with information sharing (IS) under non-stationary stochastic demand with service-level constraints. For this purpose, we utilize mixed-integer linear programming formulations to quantify the benefits that can be accrued by a supplier, multiple retailers and the system as a whole by switching from IS to VMI. More specifically, we investigate the incremental value that VMI provides beyond IS in terms of expected cost savings, inventory reductions, and decrease in shipment sizes from the supplier to the retailers by conducting a large number of computational experiments. Results reveal that the decision transfer component of VMI improves these performance measures significantly when the supplier׳s setup cost is low and order issuing efficiency is high. The benefits offered by VMI are negligible under the problem settings where the supplier׳s order issuing efficiency is low and the production setup serves solely a single replenishment under IS.