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...

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...

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...

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