The latter two models are stochastic and account for uncertainty regarding the status and controllability of certain flights. The first stochastic model is scenario based, while the second relies on a ...

In this paper we consider ambiguous stochastic constraints under partial information consisting of means and dispersion measures of the underlying random parameters. Whereas the past literature used ...

This paper develops a stochastic optimization model to perform efficient execution that considers secondary marketing functionality including loan-level efficient execution, guarantee fee buy-up or ...

This work proposes a generic calibration framework to both vanilla and no-touch options for a large class of continuous semi-martingale models. The method combines a forward equation for barrier ...

The Stochastic Optimization Model is being used to address disaster scenarios, including the management of resources to battle giant wildfires and grapple with pandemics.

In this white paper, written in collaboration with Principal Data Scientist Alan McCord, Coupa outlines a grounded, scalable approach to AI in supply chain design and planning.