An innovative simultaneous stochastic optimization approach is proposed that combines actor-critic reinforcement learning and stochastic mathematical progr...

This paper presents a multiobjective, mixed-integer linear programming (MILP) model that integrates production scheduling, inventory management, and vessel a...

The parameter configuration problem consists of finding a parameter configuration that provides the most effective performance by a given algorithm. This pap...

The most common form of renewable energy production around the world is hydropower. As a result of the growing demand for robust and environmentally friendly...

We consider online optimization problems with time-varying linear equality constraints. In this framework, an agent makes sequential decisions using only pri...

Hydropower producers participate in the electricity market by providing bids in the day-ahead market auctions. Making good bids that obey all market rules an...

This paper studies the properties of a stochastic optimization model for the short-term hydropower generation problem with uncertain inflows. The uncertaint...

In an effort to reduce power system-caused wildfires, utilities carry out public safety power shutoffs (PSPS) in which portions of the grid are de-energized ...

The short-term scheduling of activities in underground mines is an important step in mining operations. This procedure is a challenging optimization problem ...

Hybrid renewable energy systems (HRES), which co-locate two or more renewable energy sources, have proven to be promising frameworks for harnessing complemen...

Statistical learning models are proposed for the prediction of the probability of a spike in the electricity DART (day-ahead minus real-time price) spread. A...

We explore the realized alpha-performance heterogeneity in green and brown stocks' universes using the peer performance ratios of Ardia and Boudt(2018). Focu...

Using a multi-level perspective approach combined with top-down macroeconomic models, we analyse the situation of the GCC countries in the perspective of a...

We assess different scenarios for a transition to zero-net emissions in Qatar. The key technologies involved in the transition include electric mobility, hyd...

The Generator Maintenance Scheduling Problem (GMSP) is a problem that combines a hydropower optimization problem with a scheduling problem. Both problems are...

We consider a discrete-time version of the fish war model, where a regulator imposes a moratorium on fishing activities whenever the stock reaches a predeter...

Every component of an electric power system is susceptible to failure. The power transmission system connects generating units to local distribution systems,...

We formulate a batch reinforcement learning-based demand response approach to prevent distribution network constraint violations in unknown grids. We use the...

Engineering design is often faced with uncertainties, making it difficult to determine an optimal design. In an unconstrained context, this amounts to choose...

The simultaneous stochastic optimization of mining complexes (SSOMC) is a large-scale stochastic combinatorial optimization problem that simultaneously manag...