Optimizing static risk-averse objectives in Markov decision processes is challenging because they do not readily admit dynamic programming decompositions. Pr...

Seaports are highly vulnerable to climate-change induced events, which makes it necessary for them to invest in climate change adaptation measures to ensure ...

For planning the operation of power transmission systems, which transport the energy produced by generation plants to customers centers, it is essential to e...

This paper first presents a time-series impact analysis of charging electric vehicles (EVs) to loading levels of power network equipment considering stochast...

In this paper, we investigate the problem of system identification for autonomous Markov jump linear systems (MJS) with complete state observations. We prop...

This paper presents a novel rapid estimation method (REM) to perform stochastic impact analysis of grid-edge technologies (GETs) to the power distribution ne...

The estimation of the structural model poses a major challenge as its underlying asset (the firm's asset value) is not directly observable. We extend the m...

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

In multi-robot missions, relative position and attitude information between robots is valuable for a variety of tasks such as mapping, planning, and formatio...

Recommender systems provide recommendations to their users for items and services by creating a model tailored to each user to infer their preferences based ...

Motivated by our collaboration with one of the largest fast-fashion retailers in Europe, we study a two-echelon inventory control problem called the One-Ware...

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...

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

We use stochastic dynamic programming to design and solve an extended structural setting for which the illiquidity of the firm's assets under liquidation i...

In this paper, we study a novel approach for data-driven decision-making under uncertainty in the presence of contextual information. Specifically, we addres...

This research focuses on the bid optimization problem in the real-time bidding setting for online display advertisements, where an advertiser, or the adverti...

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

Position estimation in Multi-Robot Systems (MRS) relies on relative angle or distance measurements between the robots, which generally deteriorate as dista...

The multi-depot scheduling problem (MDVSP) is one of the most studied problem in public transport service planning. It consists of assigning buses to each ti...