In this paper we discuss multistage programming with the data process subject to uncertainty. We consider a situation where the data process can be naturally separated into two components: one can be ...

Abstract: Models are built to help represent, understand, and further characterize physical systems. In addition, the ubiquitous presence of uncertainties in material properties, geometry, and loading ...

Abstract: The increasing power of computing platforms and the recent advances in data science techniques have fostered the development of data-driven computational models of engineering systems with ...

Optimization under uncertainty typically requires a probability distribution of the uncertain parameters and/or variables. While this approach has successfully solved many problems, its success is ...

Editor's Note: This article first appeared in the September 2024 issue of Supply Chain Management Review. For more content like this, click here to subscribe to either the print or digital edition of ...