This paper presents a novel partially distributed outer approximation algorithm, named PaDOA, for solving a class of structured mixed integer convex programming problems to global optimality. The proposed scheme uses an iterative outer approximation method for coupled mixed integer optimization...

This paper discusses the theoretical and practical aspects of new methods for solving DEA problems under real-life geometrical uncertainty and probability uncertainty of sample data. The proposed minimax approach to solve problems with geometrical uncertainty of sample data involves an...

Greenhouse gas policies confront the trade-off between the costs of reducing emissions and the benefits of avoided climate change. The risk of uncertain and potentially irreversible catastrophes is an important issue related to the latter, and one that has not yet been well incorporated into...

Practitioners in the electricity industry aim to assess the value of power plants or other real options several months or even years ahead of operation. Such a valuation is notably required for hedging purposes. The revenue streams to be earned in the spot market are thereby already secured on...

This paper proposes two stochastic programming models for master production scheduling with capacity-load factor scenarios. In contrast to other work on production planning with load-dependent lead times or dynamic capacity loads, we iteratively build a set of realistic capacity-load factor...

We propose a fully data-driven approach to calibrate local stochastic volatility (LSV) models, circumventing in particular the ad hoc interpolation of the volatility surface. To achieve this, we parametrize the leverage function by a family of feed-forward neural networks and learn their...

The recent evolution of prudential regulation establishes a new requirement for banks and supervisors to perform reverse stress test exercises in their risk assessment processes, aimed at detecting default or near-default scenarios. We propose a reverse stress test methodology based on a...

In the present paper, we investigate the Merton portfolio management problem in the context of non-exponential discounting, a context that gives rise to time-inconsistency of the decision-maker. We consider equilibrium policies within the class of open-loop controls that are characterized, in...

We model a risk-averse firm owner who wants to maximize the intertemporal expected utility of firm’s dividends. The optimal dynamic control problem is characterized by two stochastic state variables: the equity value, and profitability (ROA) of the _rm. According to the empirical evi-dence, we...

We develop a stochastic optimization model for scheduling a hybrid solar-battery storage system. Solar power in excess of the promise can be used to charge the battery, while power short of the promise is met by discharging the battery. We ensure reliable operations by using a joint chance...