### 114 Papers in 2018

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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...

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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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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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In this paper, we propose an intuitive way to couple several dynamic time series models even when there are no innovations. This extends previous work for m...

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Microgrid, a promising component of smart grid, will potentially yield a free electricity market. This paper proposes a novel construction for a community mi...

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Algorithms for finding sparse solutions of underdetermined systems of linear equations have been the subject of intense interest in recent years, sparked b...

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The airline crew scheduling problem involves determining schedules for airline crew members such that all the scheduled flights over a planning horizon (usua...

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For the past few years, the mining industry has seen a lot of operational changes. Digitalization and automation of many processes have paved the way for an ...

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The paper combines two major contemporary systems and control methodologies to obtain a unique $$\epsilon$$-Nash equilibrium for optimal execution problem...

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In its reform of the US bankruptcy procedure, the American Bankruptcy Institute (ABI) is proposing to grant a redemption option to junior creditors and let...

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Electrical distribution network operators require measurements from phasor measurement units (PMUs), micro-PMUs ($$\mu$$PMUs), and smart meters (SMs) in or...

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This paper investigates the current patient transportation between services in a large hospital and provides a simulation-optimization solution to reduce com...

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The Integral Simplex Using Decomposition (ISUD) algorithm has been developed recently to solve large set partitioning problems (SPPs) in a primal way, i.e.,...

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This paper develops an exact method for the redundancy allocation problem (RAP) for multistate homogeneous series-parallel systems. The problem aims to min...

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We consider a class of dynamic collective choice models with social interactions, whereby a large number of non-uniform agents have to individually settle ...

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The primal adjacency-based algorithm and the multi-directional dynamic programming algorithm are two exact methods that have recently been developed to effic...

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Top-tier customers -that is, those 20% of customers that typically bring in 80% of all profits- are extremely valuable to companies. In the many instances ...

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The optimal reactive power dispatch (ORPD) problem is an alternating current optimal power flow (ACOPF) problem where discrete control devices for regulating...

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In this paper, we study the problem of responsibility sharing for product recovery, and its relation to the design of Extended Producer Responsibility (EPR) ...

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In this paper we tackle the problem of eNodeB failure detection in LTE networks using Binary Classification techniques under smart-cities Machine-to-Machine ...

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In this paper, we develop algorithmic approaches for a recently defined class of games, the integer programming games. Two general methods to approximate an...

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A hyper-heuristic refers to a search method or a learning mechanism for selecting or generating heuristics to solve computational search problems. Operat...

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In the recent years, the development of new algorithms for multiobjective optimization has considerably grown. A large number of performance indicators has...

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We consider the problem of efficiently managing a fishery where pollution externalities are present. The open-access bionomic model is analyzed in an $$n$$...

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Facility networks can be disrupted by, for example, power outages, poor weather conditions, or natural disasters, and the probabilities of these events may b...

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New digital technologies including the development of advanced sensors and monitoring devices have enabled a mining complex to acquire new information abou...

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Mining complexes are value chains where extracted material from different mines is transformed into sellable products through a set of processing streams. ...

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High-order sequential simulation methods have been developped as an alternative to existing frameworks to facilitate the modelling of spatial complexity of...

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A mining complex can include multiple mines, stockpiles, waste dumps and processing facilities. Traditional optimization approaches are often based on sequ...

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Over the last decade, geological uncertainty, its effects on long-term mine planning and methods for related risk management have been studied. However, th...

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A new non-stationary, high-order sequential simulation method is presented herein, aiming to accommodate complex curvilinear patterns and high-order spatia...

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Multiple-point simulations have been introduced over the past decade to overcome the limitations of second-order stochastic simulations in dealing with geolo...

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We study an integrated process configuration, lot-sizing, and scheduling problem, which appears in a real production environment in the packaging industry. P...

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The eccentric connectivity index of a connected graph $$G$$ is the sum over all vertices $$v$$ of the product $$d_G(v)e_G(v)$$, where $$d_G(v)$$ is ...

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Genetic algorithms are used for feature selection through a fitness function that drives the evolution of populations. With parallel universes, an importance...

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This paper addresses the problem of distributing uniformly infrared radiative energy intercepted by a thermoplastic sheet surface during the infrared radiati...

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A new solution approach is developed herein to address the topic of multi-product open-pit mine production scheduling with multi-element uncertainty. The m...

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In this paper, we consider non-stationary response variables and covariates, where the marginal distributions and the associated copula may be time-dependent...

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We present a new strategic multi-period optimization problem for the siting of electric vehicle (EV) charging stations. One main novelty in this problem is t...

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We consider a two-stage stochastic discrete program in which some of the second stage constraints involve expectations that cannot be computed easily and a...

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We consider the multivariate linear model for multilevel data where units are nested within a hierarchy of clusters. We propose permutation procedures to tes...

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This paper addresses combinatorial optimization problems under uncertain and correlated data where the mean-covariance information of the random data is assu...

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There has been a lot of interest recently on the energy efficiency and environmental impact of wireless networks. Given that the base stations are the netw...

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In this paper, we consider a two-species fishery model where the species can have different biological interactions, namely, competitive, symbiotic or prey...

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Given a directed graph $$G=(V,A)$$, capacity and cost functions on $$A$$, a root $$r$$, a subset $$T \subset V$$ of terminals, and an integer $$k$$...

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A graceful difference labeling (gdl for short) of a directed graph $$G$$ with vertex set $$V$$ is a bijection (f:V\rightarrow{1,\ldots,\vert V\vert}...

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The eccentricity of a vertex $$v$$ in a graph $$G$$ is the maximum distance between $$v$$ and any other vertex of $$G$$. The diameter of a graph (...

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We extend a quasi-Monte Carlo scheme designed for coagulation to the simulation of the coagulation-fragmentation equation. A number $$N$$ of particles is ...

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We address a three-level lot sizing and replenishment problem with a distribution structure (3LSPD), which is an extension of the one-warehouse multi-retaile...

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Smart homes have the potential to achieve optimal energy consumption with appropriate scheduling. It is expected that 35% of households in North America an...

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Personnel scheduling aims at determining the cheapest work schedules to cover the demand for one or more tasks at each period of a given horizon. During the ...

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The Time Window Assignment Vehicle Routing Problem (TWAVRP) is the problem of assigning time windows for delivery before demand volume becomes known. This i...

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This article describes a new model aiming at optimizing short- and medium-term underground mine scheduling. The complexity of the problem to solve and the fr...

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We consider an integrated planning problem that combines production, inventory and inbound transportation decisions in a context where several suppliers each...

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In this paper we propose C-VNS (Continuous variable neighborhood search) method for finding all solutions to a nonlinear system of equations (NSE). We tran...

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This paper proves the concept that it is feasible to accurately recognize specific human mobility shared patterns, based solely on the connection logs betw...

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Generally, the semiclosed-form option pricing formula for complex financial models depends on unobservable factors such as stochastic volatility and jump int...

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In the field of Automatic Programming (AP), the solution of a problem is a program, which is usually presented by a tree with a specific structure. This tree...

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The parallel space decomposition of the Mesh Adaptive Direct Search algorithm (PSD-MADS proposed in 2008) is an asynchronous parallel method for constrained ...

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This paper targets a stochastic energy management problem. We first decouple the stochasticity of the global scenarios to local scenarios. Then, we use spat...

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We describe LNLQ for solving the least-norm problem $$\min\ \|x\|$$ subject to $$Ax=b$$. Craig's method is known to be equivalent to applying the conjug...

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Vehicle routing problems (VRPs) are among the most studied problems in operations research. Nowadays, the leading exact algorithms for solving many classes o...

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This paper studies the strategic behavior of firms competing in the exploitation of a common-access productive asset, in the presence of pollution external...

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It is well known that strategic consumers can harm firms' profits by delaying their purchases, to buy at discounted price. A retailer can induce consumers ...

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In this paper, we address a personalized multi-department multi-day shift scheduling problem with a multi-skill heterogeneous workforce where employees can b...

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Maintenance of power generators is essential for reliable and efficient electricity production. Because generators under maintenance are typically inactive, ...

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Recent progress in energy storage have contributed to create large-scale storage facilities and to decrease their costs. This may bring economic opportunitie...

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Derivative-free optimization (DFO) is the mathematical study of the optimization algorithms that do not use derivatives. One branch of DFO focuses on model-...

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Metros and other rapid transit systems increase the mobility of urban populations while decreasing congestion and pollution. There are now 187 cities with a ...

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We consider the problem of pricing and advertising a one-time entertainment event. We assume that the organizers want to sell all available tickets. Thre...

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Nanotherapy represents a promising approach to target tumors with anticancer drugs while minimizing systemic toxicity. Evaluation of nanoparticle (NP) design...

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The paper presents a model for the characterization of M2M traffic and the performance evaluation of LTE access to support M2M communication, embedded into ...

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We consider the maximum $$k$$-cut problem that involves partitioning the vertex set of a graph into $$k$$ subsets such that the sum of the weights of the...

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This paper focuses on the traveling salesman problem with time windows (TSPTW) that arises in postal services and parcel deliveries and has features differin...

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In this paper, we present an online reinforcement learning algorithm, called Renewal Monte Carlo (RMC), for infinite horizon Markov decision processes with ...

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Clustering is the subject of active research in several fields such as operations research, statistics, pattern recognition, and machine learning. The range ...

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We study the behavior of a generalized splitting method for sampling from a given distribution conditional on the occurrence of a rare event. The method retu...

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In emergency call centers (for police, firemen, ambulances, rescue teams) a single event can sometimes trigger many incoming calls to the center in a short p...

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Stochastic programming and distributionally robust optimization seek deterministic decisions that optimize a risk measure, possibly in view of the most adv...

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In this paper, we establish the maximum number of basic shortest paths in Cartesian product graphs and bounds on the maximum number of the vertex-disjoint sh...

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The mesh adaptive direct search (MADS) algorithm is designed for blackbox optimization problems for which the functions defining the objective and the constr...

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The purpose of this study is to design incentives for price and advertising coordination in a bilateral monopoly. I prove that a wholesale price reduction ...

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Employee scheduling is an important activity in the service industry as it has a significant impact on costs, sales, and profitability. While a large amount ...

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Vehicle scrappage subsidy programs have been widely applied by governments to replace old cars by newer, more fuel-efficient ones. While these programs hav...

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This paper introduces two classes of location problems with interconnected facilities. These problems differ from classical location problems in the sense ...

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We survey basic ideas and results on randomized quasi-Monte Carlo (RQMC) methods, discuss their practical aspects, and give numerical illustrations. RQM...

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We study the behavior of a generalized splitting method for sampling from a given distribution conditional on the occurrence of a rare event. The method retu...

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Clustering is an automated and powerful technique for data analysis. It aims to divide a given set of data points into clusters which are homogeneous and/o...

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We consider a network whose links have random capacities and in which a certain target amount of flow must be carried from some source nodes to some destina...

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Random number generators were invented before there were symbols for writing numbers, and long before mechanical and electronic computers. All major civiliza...

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Parrondo's paradox is extended to regime switching random walks in random environments. The paradoxical behavior of the resulting random walk is explained...

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This paper addresses the winner determination problem (WDP) for TL transportation procurement auctions under uncertain shipment volumes and uncertain carrier...

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This paper focuses on designing a state estimator for a discrete-time SEIR epidemic model of an influenza-like illness. It is assumed that only sets of adm...

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We analyze a transboundary pollution differential game where, in addition to the standard temporal dimension, a spatial dimension is introduced to capture th...

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The third installment of the Basel Accords advocates a capital charge against Credit Valuation Adjustment (CVA) variability. We propose an efficient numeri...

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Wrong-way risk arises when the value of a financial transaction is adversely correlated with the creditworthiness of the counterparty. This paper investiga...

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The vertex $$p$$-center problem consists in selecting $$p$$ centers among a finite set of candidates and assigning a set of clients to them, with the aim...

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We investigate surrogate-assisted strategies for global derivative-free optimization using the mesh adaptive direct search MADS blackbox optimization algorit...

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We use NORTA (NORmal To Anything) to enhance normal credit-risk factor settings in modeling common risk factors and capturing contagion effects...

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For the last decades, community detection is a well-studied problem because it has applications in various fields. Variable Neighborhood Search (VNS) is an e...

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The shortest path problem with resource constraints finds the least cost path between two nodes in a network while respecting constraints on resource consump...

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We propose an infeasible interior-point algorithm for constrained linear least-squares problems based on the primal-dual regularization of convex program...

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The $$P_k$$-hitting set problem consists in removing a minimum number $$\psi_k(G)$$ of vertices of a given graph $$G$$ so that the resulting graph does...

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The shortest path problem with resource constraints (SPPRC) is often used as a subproblem within a column generation approach for routing and scheduling prob...

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Energy and the environment are closely interconnected. In particular, energy-related carbon dioxide emissions are major contributors to climate change. To an...

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We propose a factorization-free method for equality-constrained optimization based on a problem in which all constraints are systematically regularized. ...

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The Canadian province of Quebec has set for 2030 a greenhouse gas (GHG) emission reduction target of 37.5% below 1990 levels. Meeting such a reduction targ...

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The classical alternating current optimal power flow problem is highly nonconvex and generally hard to solve. Convex relaxations, in particular semidefinite,...

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The classical p-median problem assumes that service to customers is always provided by the closest facility, while in practice, customers often interact for...

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