In this paper, we consider the newsvendor model under partial information, i.e., where the demand distribution D is partly unknown. We focus on the classical case where the retailer only knows the expectation and variance ...

Maximum entropy methods are used to infer the true trip-distribution matrix in cases where parts of the data are suppressed due to privacy concerns. Large proportions of the suppressed data are found to be inferred correctly ...

This paper deals with the use of gravity models to examine journeys-to-work. The purpose of the paper is to study very simple examples demonstrating that gravity models may be subject to serious misspecification in aggregate ...

In this paper we consider statistical distributions of different types of patients on the patient lists of doctors. In our framework different types of patients have different preferences regarding their preferred choice ...

In this paper we present empirical results based on a network model for commuting flows. The model is a modified version of a construction introduced in Thorsen et al. (1999). Journeys-to-work are determined by distance ...

Supply channels typically face uncertain and time-varying demand. Nonetheless, time-dependent channel optimization while addressing uncertain demand has received limited attention due to the high level of complexity of the ...

Almost every vendor faces uncertain and time-varying demand. Inventory level and price optimization while catering to stochastic demand are conventionally formulated as variants of newsvendor problem. Despite its ubiquity ...

In this paper we develop a new simulation procedure that can be used to examine validity of model extensions. Our testing regime is carried out on a number of different trip distribution models. We test the models on ...

In this paper we study bulk shipping of coal between the central regions in the world. We compare the performance of cost-minimizing models with a gravity model approach. The main nding in the paper is that cost minimizing ...