Faster delivery, lower shipping costs, and a higher chance of product availability, are some of the benefits offered by an omnichannel business model. Assumi...

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

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

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...

In the Weighted Fair Sequences Problem (WFSP), one aims to schedule a set of tasks or activities so that the maximum product between the largest temporal dis...

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

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

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

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

We formulate an efficient approximation for multi-agent batch reinforcement learning, the approximated multi-agent fitted Q iteration (AMAFQI). We present a ...

We study a predisaster relief network design problem with uncertain demands. The aim is to determine the prepositioning and reallocation of relief supplies. ...