In this paper exponential distribution is implemented as a demand distribution in newsvendor model with two different and conflicting goals. The first goal is the standard objective of maximization of the expected profit. The second one is to maximize the probability of exceeding the expected profit, called survival probability. Using exponential distribution as the demand distribution allows u...

We consider robust stochastic optimization problems for risk-averse decision makers, where there is ambiguity about both the decision maker's risk preferences and the underlying probability distribution. We propose and analyze a robust optimization problem that accounts for both types of ambiguity. First, we derive a duality theory for this problem class and identify random utility functions as...

The single-product, single-period newsvendor problem with two decision variables, namely price and stock quantity, is considered. The performance measure, in addition to the expected revenue, includes the variance of the income scaled with a risk parameter. We present conditions for the concavity of this risk-sensitive performance measure and the uniqueness of the optimal solution for both risk...

We consider a repeated newsvendor problem where the decision-maker (DM) does not have access to the underlying distribution of discrete demand. We analyze three informational settings: i.) the DM observes realized demand in each period; ii.) the DM only observes realized sales ; and iii.) the DM observes realized sales but also a lost sales indicator that records whether demand was censored or ...

Short abstract Past experimental studies of decision-making in the context of the Newsvendor problem unanimously find that the decision-makers tend to make suboptimal decisions and, unless special measures are taken to induce “in-task” learning, fail to improve quality of their decisions over time. However, most of these past studies dealt with individual decision-makers. In the present study w...

This paper examines a single-period inventory problem with random capacity and demand, where the loss-averse preference is adopted to describe the newsvendor’s decision-making behavior. When the loss-averse newsvendor orders, the supplier has some random replenishment capacity. He will choose an order quantity to maximize his expected utility. The newsvendor’s optimal ordering policy is obtaine...

We develop a procedure for testing the quality of a candidate solution for a class of stochastic programs. Quality is defined via the optimality gap and the procedure’s output is a confidence interval on this gap. We review a multiple-replications procedure and then, we present a result that justifies a computationally simplified single-replication procedure. We compare empirical coverage resul...

We investigate learning-by-doing in the newsvendor inventory problem. An earlier study observed that decision makers tend to anchor their orders around average demand and fail to adjust sufficiently towards the expected profit-maximizing order. Principles of behavioral theory suggest some relatively simple interventions into the decision maker’s experience and feedback that might improve perfor...

We consider the problem of optimizing inventories for problems where the demand distribution is unknown, and where it does not necessarily follow a standard form such as the normal. We address problems where the process of deciding the inventory, and then realizing the demand, occurs repeatedly. The only information we use is the amount of inventory left over. Rather than attempting to estimate...

T newsvendor model is designed to decide how much of a product to order when the product is to be sold over a short selling season with stochastic demand and there are no additional opportunities to replenish inventory. There are many practical situations that reasonably conform to those assumptions, but the traditional newsvendor model also assumes a fixed salvage value: all inventory left ove...