We consider a firm offering an opaque good over one selling season, that is, a product whose full characteristics are only revealed after the consumer comp...

This paper studies disjunctive cutting planes in Mixed-Integer Conic Programming. Building on conic duality, we formulate a cut-generating conic program for...

We consider the iterative solution of regularized saddle-point systems. When the leading block is symmetric and positive semi-definite on an appropriate sub...

The accessibility and reducing cost of distributed renewable energy sources are stimulating the emergence of small-scale residential prosumers who can produc...

The smooth operation of largely deployed Internet of Things (IoT) applications will depend on, among other things, effective infrastructure failure detectio...

This paper proposes a detailed analysis of the evolution of Canadian energy systems under some selected EMF (Energy Modeling Forum) 34 scenarios. Our analysi...

Overbooking is a common practice in the air cargo industry because booked and actual demands often differ greatly. As a consequence, in case of excessive ove...

We analyze a differential game with spatially distributed controls to study a multiregional transboundary pollution problem. The dynamics of the state variab...

We built a time-consistent cooperative solution for the class of dynamic games played over event trees in the context where the structure of the tree is gi...

This paper presents the application of adaptive simultaneous stochastic optimization with a representative branching framework to generate the strategic pl...

We address the problem of accelerating column generation (CG) for set-covering formulations via dual optimal inequalities (DOI). DOI use knowledge of the du...

Clustering algorithms help identify homogeneous subgroups from data. In some cases, additional information about the relationship among some subsets of the d...

This paper presents an invariant Rauch-Tung-Striebel Smoother (IRTS) applicable to systems with states that are an element of a matrix Lie group. In particul...

The standard blending problem consists of combining components to produce a final product with a given demand, while satisfying specific criteria with resp...

Deploying applications having many processes in a multi-cloud environment is challenging. The cloud manager has goals such as minimizing power consumption, w...

A new mathematical model for stochastic short-term optimization of mining complexes is presented that simultaneously optimizes the short-term extraction sequ...

With sufficient layers, enough training data, enough time, and often a custom tailored architecture, modern deep learning methods can be extremely successf...

Mineral value chains or mining complexes involve mining, processing, stockpiling, waste management, and transportation activities. An integrated stochastic...

The energy landscape is marked by a rapid emergence of electricity prosumers at all levels of the grid. While energy policy seems to be more adaptive to the ...

In this paper we study the linear quadratic regulation (LQR) problem for dynamical systems coupled over large-scale networks and obtain locally computable l...

Graphon-based control has recently been proposed and developed to solve control problems for dynamical systems on networks which are very large or growing w...

Very large networks linking dynamical agents are now ubiquitous and the need to analyse, design and control them is evident. The emergence of the graphon the...

In derivative-free and blackbox optimization, the objective function is often evaluated through the execution of a computer program seen as a blackbox. It ...

The integral column generation algorithm (ICG) was recently introduced to solve set partitioning problems involving a very large number of variables. This pr...

This work introduces StoMADS, a stochastic variant of the mesh adaptive direct-search (MADS) algorithm originally developed for deterministic blackbox optim...

Nanoparticle-mediated drug delivery may be a promising alternative to traditional chemo-therapy of high systemic toxicity. Tumor tissue architecture poses a ...

We propose a generalized decomposition approach for production planning problems with process configuration decisions. These problems appear in contexts wher...

This paper studies the team orienteering problem, where the arrival time and service time affect the collection of profits. Such interactions result in a non...

This work proposes strategies to handle three types of constraints in the context of blackbox optimization: binary constraints that simply indicate if they a...

Maritime Guinea is subject to the development of numerous mineral ports enabling the benefits of the mining sector to be fully realized. However, in Guinea...

A highly influential ingredient of many techniques designed to exploit sparsity in numerical optimization is the so-called chordal extension of a graph repre...

In this paper, we solve a rich real-word Multi-Depot Multi-Period Petrol Replenishment Problem with a heuristic based on Branch-and-Price heuristic. The netw...

The complex-step derivative approximation is a numerical differentiation technique that can achieve analytical accuracy, to machine precision, with a single ...

Production planners in the non-ferrous metal industry face an inherent combinatorial complexity of the metal production process within a fast changing market...

This article discusses the precedence-constrained class sequencing problem (PCCSP). In scheduling terms, this is a one-machine scheduling problem with preced...

This paper presents a linear mixed-integer formulation to solve the short-term unit commitment problem. It determines the pair of maximum efficiency points o...

In this paper, we compare the BFGS and the conjugate gradient (CG) methods for solving unconstrained problems with a trust-region algorithm. The main result ...

In an optimization problem, multiplying an inequality constraint by a positive scalar has no effect on the domain. However, such a transformation might have...

Cities are facing severe traffic-related problems causing emission thresholds to be exceeded. All around the world, city center access restriction policies a...

We determine optimal pricing and order quantity of two substitute products in two markets, one of them is seasonal, with a decreasing market potential over...

We introduce an iterative method named BiLQ for solving general square linear systems \(Ax=b\) based on the Lanczos biorthogonalization process defined by ...

Dealing with demand uncertainty in multi-item lot sizing problems poses huge challenges due to the inherent complexity. The resulting stochastic formulation...

A small polygon is a polygon of unit diameter. The question of finding the largest area of small \(n-\)gons has been answered for some values of \(n\)....

In the present paper, we prove lower and upper bounds for each of the ratios \(GA/\delta\), as well as a lower bound on \(GA/\sqrt{\delta}\), in terms of...

We consider the use of demand response to address phase unbalance in a distribution grid. At present this problem is addressed by modifying the topology of t...

Statistical image reconstruction in X-Ray computed tomography yields large-scale regularized linear least-squares problems with nonnegativity bounds, where t...

We introduce the conditional \(p\)-dispersion problem (c-pDP), an incremental variant of the \(p\)-dispersion problem (pDP). In the c-pDP, one is given a...

In e-commerce warehouses, online retailers increase their efficiency by using a mixed-shelves (or scattered storage) concept, where unit loads are purposeful...

Variable fixing by reduced costs is a popular technique for accelerating the solution process of mixed-integer linear programs. For vehicle routing problems ...

The performance of deep neural networks is highly sensitive to the choice of the hyperparameters that define the structure of the network and the learning pr...

We present a progressive approximation algorithm for the exact solution of several classes of interdiction games in which two non-cooperative players (namely...

We consider a large group of consumers who can choose between two products at each purchasing occasion. Their choice is influenced by the marketing strateg...

The 1970s-1980s droughts in the Sahel caused a significant degradation of land and plant cover. To cope with this situation, populations have developed seve...

Personnel scheduling consists of determining least-cost work schedules to cover the demand of multiple jobs expressed in number of employees per job and peri...

We address a stochastic three-level lot sizing and replenishment problem with a distribution structure in a two-stage decision process. We consider one produ...

The introduction of renewable energy sources (RES) changes the shape of an electricity system's supply curve. In a perfectly competitive market, this causes ...

This paper explores the idea that two-stage worst-case regret minimization problems with either objective or right-hand side uncertainty can be reformulated ...

Mathematical models of energy-economy-environmental systems (E3) provide a rational framework for exploring the effects of energy and climate policies and su...

Since nonprofit organizations play an important role in providing goods and services in all countries, this paper aims at determining optimal policies for ...

Significant progress has been made in the field of computer vision, due to the development of supervised machine learning algorithms, which efficiently extra...

This paper introduces the algorithmic design and implementation of Tulip, an open-source interior-point solver for linear optimization. It implements the ho...

In this study, we develop a deterministic nonlinear filtering algorithm based on a high-dimensional version of Kitagawa (1987) to evaluate the likelihood fun...

Array-RQMC has been proposed as a way to effectively apply randomized quasi-Monte Carlo (RQMC) when simulating a Markov chain over a large number of steps to...

In this paper, we introduce a class of deterministic finite-horizon two-player non-zero-sum differential games where one player uses continuous control wh...

Estimating the unknown density from which a given independent sample originates is more difficult than estimating the mean, in the sense that for the best po...

Intermittent renewable energy, such as solar and wind, brings uncertainty into the grid. To increase their contribution into the energy mix, load management ...

User-centered logistics aiming at customer satisfaction are gaining importance due to growing e-commerce and home deliveries. Customer satisfaction can be ...

Reducing the number of features used in data classification can remove noisy or redundant features, reduce the cost of data collection, and improve the accur...

In this paper, we study the competition between national brands and private labels (or store brands) by analyzing the impacts of their presence on strategies...

We consider three colouring problems which are variations of the basic vertex-colouring problem, and are motivated by applications from various domains. We g...

We analyze an endogenous growth model with non-constant discounting and a negative externality of growth on utility. With a decreasing rate of impatience, ...

The deepening penetration of renewable power generation is challenging how the minute balancing of supply and demand is carried out by power system operators...

Randomized decision making refers to the process of taking decisions randomly according to the outcome of an independent randomization device such as a dic...

This paper considers a dynamic Emergency Medical Services (EMS) network design problem and introduces two novel two-stage stochastic programming formulatio...

Drawing on statistical learning theory, we derive out-of-sample and optimality guarantees about the investment strategy obtained from a regularized portfoli...

We present a case study of using machine learning classification algorithms to initialize a large scale commercial operations research solver (GENCOL) in the...

We consider a class of min-max robust problems in which the functions that need to be robustified can be decomposed as the sum of arbitrary functions. This...

In large commercial airlines, the monthly schedule (roster) of the crew members is usually determined by solving two problems sequentially, namely, the crew ...

We build upon Estrin et al. (2019) to develop a general constrained nonlinear optimization algorithm based on a smooth penalty function proposed by Fletch...

\(K\)-medoids clustering is among the most popular methods for cluster analysis, but it carries several assumptions about the nature of the latent clusters...

This paper studies the Dynamic Facility Location Problem with Modular Capacities (DFLPM). We propose a linear relaxation based heuristic (LRH) and an evoluti...

The minimum residual method (MINRES) of Paige and Saunders (1975), which is often the method of choice for symmetric linear systems, is a generalization of t...

We consider several time series and for each of them, we fit an appropriate dynamic parametric model. This produces serially independent error terms for each...

We propose an iterative method named USYMLQR for the solution of symmetric saddle-point systems that exploits the orthogonal tridiagonalization method of Sa...

Multi-agent reinforcement learning has made significant progress in recent years, but it remains a hard problem. Hence, one often resorts to developing lea...

Computational speed and global optimality are a key need for pratical algorithms of the OPF problem. Recently, we proposed a tight-and-cheap conic relaxation...

In the Inventory Routing Problem customer demand is satisfied from inventory which is replenished with capacitated vehicles. The objective is to minimize tot...

We study the time evolution of a vertically and horizontally differentiated oligopolistic industry, where firms compete in quantity and are divided into gr...

Given \(n\) points, a symmetric dissimilarity matrix \(D\) of dimensions \(n\times n\) and an integer \(p\geq 2\), the \(p\)-dispersion problem (pD...

For nearest neighbor univariate random walks in a periodic environment, where the probability of moving depends on a periodic function, we show how to estim...

We consider a personalized employee scheduling problem with characteristics present in retail stores consisting of multiple departments. In the setting under...

The present work is in a context of derivative-free optimization involving direct search algorithms guided by surrogate models of the original problem. The...

Given a set of duties to be operated over a cyclic one-week horizon and groups of drivers with similar characteristics, the cyclic bus driver rostering probl...

Recommender systems make use of different sources of information for providing users with recommendations of items. Such systems are often based on collabor...

We are witnessing an acceleration in the uptake of renewable energy in power systems. Because of the associated variability and uncertainty of renewables, ...

We are interested in blackbox optimization for which the user is aware of monotonic behaviour of some constraints defining the problem. That is, when incr...

In demand-response programs, aggregators balance the needs of generation companies and end-users. This work proposes a two-phase framework that shaves the ag...

We propose a regularization method for nonlinear least-squares problems with equality constraints. Our approach is modeled after those of Arreckx and Orban ...

We develop a general equality-constrained nonlinear optimization algorithm based on a smooth penalty function proposed by Fletcher (1970). Although it was ...

The open-pit mine production scheduling problem aims to optimize the net present value of a mining asset. Several solution methods have been proposed to find...

Operations Research (OR) has a very important role to play in credit scoring for building models that can help the lending organization to make a good decisi...

Poorly formulated initiatives on the port planning strategy are have negative effects on the tropical coastal zone. To reduce these effects, it is importan...

Dealing with computationally-intensive calibration processes is still common in distributed hydrological modelling despite the computing power growth. Comput...

This is a two-part work. In Part I, low-cost and representative reduced-fidelity models of two versions of the HYDROTEL hydrological model are constructed, u...

Smart homes have the potential to achieve efficient energy consumption: households can profit from appropriately scheduled consumption. By 2020, 35% of all h...

In the interest of full disclosure, the reader is advised that I am biased positively towards the book considered here as I have collaborated with its first ...

Ce guide vise à présenter les différentes étapes et outils de mise en place d'un processus d'aide à la décision, au sein d'une organisation liée à la santé...

The purpose of this guide is to present steps and tools to establish a decision-aid process in an organization linked to public health. This decision-aid p...