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...

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...

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...

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...

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

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

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

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 ...

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

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...

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

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

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

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

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

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

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 ...

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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 ...

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

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

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...

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

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...

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...

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

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

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...

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

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 \(k\)...

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}...

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 `(...

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

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...

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

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 ...

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

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...

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

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...

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

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

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...

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

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

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...

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

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

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 ...

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

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

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

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

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

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...

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

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

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...

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

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

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

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...

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...

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

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...

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

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 ...

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 ...

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

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

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

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...

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...

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...

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

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

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

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...

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

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

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

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...

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

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

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...

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

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

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...

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

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

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

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...

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

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