In July 2022, I received the EURO Gold medal at the 32nd EURO Conference held in Espoo, Finland. On this occasion I was asked to deliver a 30-minute presenta...

This paper presents \(\texttt{Krylov.jl}\), a Julia package that implements a collection of Krylov processes and methods for solving a variety of linear pr...

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

This note provides a counterexample to a theorem announced in the last part of the paper Analysis of direct searches for discontinuous functions, Mathemati...

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...

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

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

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

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

Summary: We study an increasingly popular retail practice called pickup partnership that allows online retailers to offer an in-store pickup service by par...

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

Short-term production planning in mining complexes involves a series of decisions concerning activities and processes to accomplish the long-term planning ...

Variations between related images (e.g. due to motions) can caused by different independent factors. A qualified representation can decouple the underlying...

We develop a Levenberg-Marquardt method for minimizing the sum of a smooth nonlinear least-squares term \(f(x) = \tfrac{1}{2} \|F(x)\|_2^2\) and a nonsmoo...

The Twelfth Montreal IPSW took place on August 22-26, 2022, and was jointly organized by the Centre de recherches mathématiques (CRM) and the Institute for D...

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 ...

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

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...

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

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...

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 study, we investigate the best remanufacturing strategy for the original equipment manufacturer (OEM) and independent remanufacturer (IR) in an innov...

Most reinforcement learning methods for adaptive-traffic-signal-control require training from scratch to be applied on any new intersection or after any modi...

In order to improve the efficiency of the last-mile delivery system when customers are possibly absent for deliveries, we propose the idea of employing the c...

This paper presents PDENLPModels.jl a new Julia package for modeling and discretizing optimization problems with mixed algebraic and partial differential equ...

Recently equal risk pricing, a framework for fair derivative pricing, was extended to consider dynamic risk measures. However, all current implementations ei...

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

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

We study how the financial literature has evolved in scale, research team composition, and article topicality across 32 finance-focused academic journals fro...

We consider the generalized successive overrelaxation (GSOR) method for solving a class of block three-by-three saddle-point problems. Based on the necessary...

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

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

Providing the right data to a machine learning model is an important step to insure the performance of the model. Non-compliant training data instances may l...

Personnel scheduling consists in determining employee work schedules (sequences of work shifts and days off) to cover the demands of multiple jobs over a pl...

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...

Crew pairing problems (CPP) are regularly solved by airlines to produce crew schedules. The goal of CPPs is to find a set of pairings (sequence of flights 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...

The conjugate gradient (CG) method is a classic Krylov subspace method for solving symmetric positive definite linear systems. We introduce an analogous sem...

We consider the problem of training a deep neural network with nonsmooth regularization to retrieve a sparse and efficient sub-structure. Our regularizer is ...

We study an integrated multi-product production and distribution problem considering a network of multiple plants and customers, who are geographically dispe...

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...

The transmission of the contagious COVID-19 is known to be highly dependent on individual viral dynamics. Since the cycle threshold (Ct) is the only semi-qua...

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

This paper considers the pricing of a new product in the face of sophisticated consumer behaviors. At the individual level, consumers are forward-looking, wh...

In this paper, we propose a fast algorithm to compute a bound for the problem of optimizing the power of a number of users sharing a set of wireless chan...

A new factor-based representation of implied volatility surfaces is proposed. The factors adequately capture the moneyness and maturity slopes, the smile att...

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

This work proposes the integration of two new constraint-handling approaches into the blackbox constrained multiobjective optimization algorithm DMulti-MADS,...

A mathematical framework for modelling constrained mixed-variable optimization problems is presented in a blackbox optimization context. The framework intr...

We investigate the ratio \(\mathcal{I}(G)\) of the average size of a maximal matching to the size of a maximum matching in a graph G. If many maximal mat...

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

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 describe a procedure to compute a projection of \(w \in ℝ^n\) into the intersection of the so-called zero-norm ball \(k B_0\) of radius \(k\), i....

The procurement of freight services is an important element for the supply chain management of a shipper (i.e., a manufacturer or retailer) that sources tran...

We study quasi-Monte Carlo (QMC) integration of smooth functions defined over the multi-dimensional unit cube. Inspired by a recent work of Pan and Owen, we ...

We consider the problem of estimating the density of a random variable \(X\) which is the output of a simulation model. We show how an unbiased density ...

We study a staffing optimization problem in multi-skill call centers. The objective is to minimize the total cost of agents under some quality of service (Q...

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...

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