Robust optimization (RO) is a powerful mean to handle optimization problems where there is a set of parameters that are uncertain. The effectiveness of the m...

In this paper we show how to robustify the computation of equilibria in two integrated assessment models for climate change. Both models deal with the optima...

Robust optimization is a methodology that has gained a lot of attention in the recent years. This is mainly due to the simplicity of the modeling process and...

In this paper, we present a stochastic two-level optimization model whose upper-level problem depicts a wastewater treatment plant deciding on the size of co...

In this article, we characterize incentive equilibrium strategies and their credibility conditions for the classes of linear-state and linear-quadratic dynam...

In this paper we present a new rolling horizon approach for solving stochastic mixed complementarity problems (MCPs). Such a scheme allows for decision-depen...

Traditionally, the planning of operating reserve has been done in terms of capacity and linear (average) ramping requirements. On the other hand, the newly e...

We propose a quasi-analytical approach for valuing American-style options under Gaussian and double exponential jumps à la Merton (1976) and Kou (2002). Our ...

Since the financial crisis of 2007-2009, there has been a renewed interest toward quantifying more appropriately the risks involved in financial positions. P...

Portfolio credit risk models are very often constructed with correlation matrices serving as proxies for interrelations in the creditworthiness of each compa...

Cake-cutting is a metaphor for problems where a principal agent has to fairly allocate resources. Such problems cover various areas of operations research ...

Modern power systems are undergoing a transitional phase, increasingly incorporating variable generation (VG) to harness the economic and environmental benef...

Facility location decisions play a critical role in transportation planning. In fact, it has recently become essential to study how such commitment integrate...

This paper provides an investigation into an anomaly called a short squeeze, in the CBOT T-Bonds Futures Market, for the period spanning January 1985 to Se...

The optimization of open-pit mine production scheduling (OPMPS) is an intricate process due to its size and uncertainty of key input parameters. Over the las...

The buffer sizing problem in unreliable production lines is a complex combinatorial optimization problem. In the formulation of the problem, the system consi...

While there has been a surge of articles on convergence diagnostic tools for MCMC on continuous stationary distributions and ordinal state spaces, Bayesian c...

Shift scheduling when the demand for employees is stochastic is usually done in two steps. Since employees need to know their shifts before the demand is kno...

We introduce learning in a dynamic game of international pollution, with ecological uncertainty. We characterize and compare the feedback non-cooperative emi...

Simulation-and-regression algorithms have become a standard tool for solving dynamic programs in many areas, in particular financial engineering and computat...