In most retail environments, when inventory runs out, the unmet demand is lost and not observed. The sales data are effectively censored by the inventory level. Factoring this censored data effect into demand estimation and inventory control decision makes the problem difficult to solve. In this paper, we focus on developing bounds and heuristics for this problem. Specifically, we consider a fi...

Introduction The periodic-review inventory control problem with lost-sales and positive lead times is one of the most fundamental yet notoriously difficult problems in the theory of inventory management (see Zipkin (2000)). The model assumes that unmet demand at the end of each period is lost, rather than being backlogged and carried over to the next period. For example, in many retail applicat...

This study considers a duopoly market in which two competitors operate their own service-inventory systems. Both determine prices to maximize profit while considering the inventory holding cost, ordering and cost incurred by lost sales. Customers are price sensitive, customer attractiveness is expressed arrival rates. We use game theory approach formulate analyze three types of pricing games: (...

We present an integrated optimization approach to parameter estimation for discrete choice demand models where data for one or more choice alternatives are censored. We employ a mixed-integer program (MIP) to jointly determine the prediction parameters associated with the customer arrival rate and their substitutive choices. This integrated approach enables us to recover proven, (near-) global ...

We present two results to aid the numerical solution of the notoriously di¢ cult discrete-time inventory model with stochastic demands, a constant leadtime, and lost sales. First, we show that the e¤ective state space is a relatively manageable compact set. Second, we show that the optimal cost is increasing in the leadtime, and we use this fact to construct a good lower bound on the optimal-co...

We study a finite-horizon lost-sales inventory model. The demand distribution is unknown and is dynamically updated based on the previous sales data in a Bayesian fashion. We derive a samplepath representation of the first order optimality condition, which characterizes the key tradeoff of the problem. The expression allows us to see why the computation of the optimal policy is difficult and wh...

ABSTRACT We consider coordination among stocking locations through replenishment strategies that explicitly take into account lateral transshipments, i.e., transfer of a product among locations at the same echelon level. The basic contribution of our research is the incorporation of supply capacity into the traditional emergency transshipment model. We formulate the capacitated production case ...