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108 Papers in 2019

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

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

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

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

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

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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...

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

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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...

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

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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...

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

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

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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...

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

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

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

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

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

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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 ...

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

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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...

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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...

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

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

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

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

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

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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...

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

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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...

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

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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...

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

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

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

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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...

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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 ...

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

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

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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...

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

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

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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 \(n\)....

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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...

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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...

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

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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...

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

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

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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...

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

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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...

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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...

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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...

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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...

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

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

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

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

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

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

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

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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...

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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...

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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...

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

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

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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...

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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...

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

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

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

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

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

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

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

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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...

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

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

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

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

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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...

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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...

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

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

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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...

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

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

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

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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...

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

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

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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...

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

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

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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...

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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...

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

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

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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...

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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...

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

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

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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...

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

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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 ...

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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...

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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...

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