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84 Papers in 2021

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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...

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We formulate a batch reinforcement learning-based demand response approach to prevent distribution network constraint violations in unknown grids. We use the...

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With the ongoing energy transition, electric power and energy systems are becoming increasingly multi-dimensional and complex with higher levels of uncertain...

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Thermostatically-controlled loads have a significant impact on electricity demand after service is restored following an outage, a phenomenon known as cold l...

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This paper presents DCISolver.jl a new Julia package implementating the Dynamic Control of Infeasibility method (DCI), introduced by Bielschowsky & Gomes (20...

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Column generation is an iterative method used to solve a variety of optimization problems. It decomposes the problem into two parts: a master problem, and on...

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It is a challenge to sustain cooperation in a finite-horizon dynamic game. Since players generally have an incentive to deviate to their noncooperative str...

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Product recalls are often consequences of quality failures. While such failures are related to a manufacturer's or supplier's design quality, the perceived q...

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A compact operations research (OR) model is proposed to analyse the prospects of meeting the Paris Agreement targets when direct air capture technologies can...

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This study assesses the contribution of various forest-based bioenergy technologies when transitioning to a low carbon economy. A detailed modeling of differ...

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Within the context of optimization under uncertainty, a well-known alternative to minimizing expected value or the worst-case scenario consists in minimizing...

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In most Swiss municipalities, a curbside system consisting of heavy trucks stopping at almost each household is used for non-recoverable waste collection. Du...

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We review dynamic quality models both in single-agent setup and in a competitive framework. Our objectives are: (1) to give the reader a vantage point on t...

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Optimization with stochastic dominance constraints has recently received an increasing amount of attention in the quantitative risk management literature. In...

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The problem of portfolio management represents an important and challenging class of dynamic decision making problems, where rebalancing decisions need to be...

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Within a non-cooperative transboundary pollution dynamic game, we study the strategic impact of a region's investment in the adoption of a cleaner technolog...

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We analyze a capital accumulation game in a dynamic version of Cournot duopoly model of complements. In this game, firms' instant profits are discontinuous a...

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Motivated by the application of equal-risk pricing and hedging of a financial derivative, where two operationally meaningful hedging portfolio policies needs...

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We introduce an iterative method named GPMR for solving 2X2 block unsymmetric linear systems. GPMR is based on a new process that reduces simultaneously...

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The use of space through satellites is more and more important for nations, companies, and individuals. However, since the first satellite was sent up in 19...

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A piecewise constant Mayer cost function is used to model optimal control problems in which the state space is partitioned into several regions, each having ...

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In this paper, we study a distributionally robust multi-item newsvendor problem, where the demand distribution is unknown but specified with a general event-...

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In blackbox optimization, evaluation of the objective and constraint functions is time consuming. In some situations, constraint values may be evaluated in...

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The time-stamped database provided by Google traces the code contributions to Chrome browser on the period from September 2008 to January 2014. It describes ...

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A small polygon is a polygon of unit diameter. The maximal area of a small polygon with \(n=2m\) vertices is not known when \(m \ge 7\). In this paper, w...

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For a simple connected graph \(G\), let \(D(G), ~Tr(G)\), \(D^{L}(G)=Tr(G)-D(G)\), and \(D^{Q}(G)=Tr(G)+D(G)\) be the distance matrix, the diagonal m...

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Production yield can be highly volatile and uncertain, especially in industries where exogenous and environmental factors such as the climate or raw material...

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This paper presents an efficient method for extracting the second-order sensitivities from a system of implicit nonlinear equations. We design a custom aut...

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We study bin-packing and lot-sizing decisions in an integrated way. Such a problem appears in several manufacturing settings where items first need to be cu...

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We propose a tone-based event study to reveal the aggregate abnormal tone dynamics in media articles around earnings announcements. We test whether they co...

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This paper introduces the consistent production routing problem in a setting with multiple plants and products. The problem consists in finding minimum-cost ...

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This paper studies a stochastic variant of the vehicle routing problem (VRP) where both customer locations and demands are uncertain. In particular, potentia...

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For a graph \(G\), the signless Laplacian matrix \(Q(G)\) defined as \(Q(G) = D(G) + A(G)\), where \(A(G)\) is the adjacency matrix of \(G\) and `...

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The Tenth Montreal IPSW took place on August 13-27, 2020, and was jointly organized by the Centre de recherches mathématiques (CRM) and the Institute for Dat...

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We develop a trust-region method for minimizing the sum of a smooth term \(f\) and a nonsmooth term \(h\), both of which can be nonconvex. Each iteratio...

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Binary quadratic programming (BQP) is a class of combinatorial optimization problems comprising binary variables, quadratic objective functions and linear/no...

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Battery charging of electric vehicles (EVs) needs to be properly coordinated by electricity producers to maintain the network reliability. In this paper, we ...

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A small polygon is a polygon of unit diameter. The maximal width of an equilateral small polygon with \(n=2^s\) vertices is not known when \(s \ge 3\). T...

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The increasingly complex energy systems are turning the attention towards model-free control approaches such as reinforcement learning (RL). This work propos...

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In this paper we examine the stability of international environmental agreements about a (common) emissions target. By signing the agreement, the parties d...

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The geometallurgical models that predicting the throughput/comminution performance of the a processing plant often rely on rock hardness models, which are ba...

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Stope design optimization defines mineable three-dimensional material volumes to be extracted from a mineral deposit, aiming to maximize cashflows subject ...

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This paper aims to identify the sources of value created in the strategic plan of a mining complex when the adaptive simultaneous stochastic optimization of ...

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In this paper, we apply flexibility-based operational planning method to microgrid (MG) unit commitment (UC). The problem is formulated based on model predi...

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The goal of the Encyclopedia of Optimization is to introduce the reader to a complete set of topics that sh...

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We study a class of deterministic finite-horizon two-player nonzero-sum differential games where players are endowed with different kinds of controls. W...

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This work is in the context of blackbox optimization where the functions defining the problem are expensive to evaluate and where no derivatives are availabl...

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We give an overview of the state of the art on the design and implementation of random number generators for simulation and general Monte Carlo sampling in p...

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We explore the use of Array-RQMC, a randomized quasi-Monte Carlo method designed for the simulation of Markov chains, to reduce the variance when simulating...

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In this paper, we consider both first- and second-order techniques to address continuous optimization problems arising in machine learning. In the first-orde...

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The Quadratic Knapsack Problem (QKP) is a well-known combinatorial optimization problem which amounts to maximizing a quadratic function of binary variables,...

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This paper develops a strategy, using concepts from Mean Field Games, to coordinate the charging of a large population of battery electric vehicles (BEVs...

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A coloring of a graph is an assignment of colors to its vertices such that adjacent vertices have different colors. Two colorings are equivalent if they indu...

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A small polygon is a polygon of unit diameter. The maximal perimeter of a convex equilateral small polygon with \(n=2^s\) vertices is not known when `(s ...

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A small polygon is a polygon of unit diameter. The maximal perimeter and the maximal width of a convex small polygon with \(n=2^s\) sides are unknown when ...

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Optimal stopping is the problem of deciding the right time at which to take a particular action in a stochastic system, in order to maximize an expected rewa...

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Distance metric learning algorithms aim to appropriately measure similarities and distances between data points. In the context of clustering, metric learnin...

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A small polygon is a polygon of unit diameter. The maximal area of a small polygon with \(n=2m\) vertices is not known when \(m\ge 7\). Finding the large...

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A small polygon is a polygon of unit diameter. The maximal perimeter and the maximal width of a convex small polygon with \(n=2^s\) vertices are not known ...

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We consider the problem of scheduling maintenance for a collection of machines under partial observations when the state of each machine deteriorates stochas...

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To satisfy a rising demand, agricultural practices have shifted from the organic fertilization of soils to intensive and highly specialized farming that uses...

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NOMAD is software for optimizing blackbox problems. In continuous development since 2001, it constantly evolved with the integration of new algorithmic...

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The primal simplex algorithm is still one of the most used algorithms by the operations research community. It moves from basis to adjacent one until optimal...

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We study the average number \(A(G)\) of colors in the non-equivalent colorings of a graph \(G\). We show some general properties of this graph invariant ...

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An innovative strategic mine planning approach is applied to a multi-mine and multi-process gold mining complex that simultaneously considers feasible capita...

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This article presents a novel stochastic optimization model that simultaneously optimizes the short-term extraction sequence, shovel relocation, scheduling o...

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A training-image free, high-order sequential simulation method is proposed herein, which is based on the efficient inference of high-order spatial statistics...

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The existing technologies that update geostatistically simulated models of mineral deposits cannot self-learn from incoming new information generated in oper...

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This paper presents a new truck dispatching policy approach that is adaptive given different mining complex configurations in order to deliver supply materia...

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Industrial mining complexes can be optimized using simultaneous stochastic optimization (SSO), which manages the risks associated with meeting production tar...

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Geostatistically simulated representations of mineral deposits are used for resource/reserve assessments, mine design and production planning, project evalua...

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A new linear model is presented herein to optimize strategic production scheduling of an open pit mine with multiple processing streams while accounting for...

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Robotic process automation (RPA) is used in various fields of human activity in order to implement faster and more secure processes through a reduction in th...

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Drones have been getting more and more popular in many economy sectors. Both scientific and industrial communities aim at making the impact of drones even mo...

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The structural model of Merton (1974) gives rise to multiple applications and extensions in corporate credit-risk analysis. The estimation of this fram...

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The spread of an infectious disease such as COVID-19 is governed by complex social interactions that are challenging to model. Policy makers must take measur...

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The Bell numbers count the number of different ways to partition a set of \(n\) elements while the graphical Bell numbers count the number of non-equivalen...

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Optimizing the hyperparameters and architecture of a neural network is a long yet necessary phase in the development of any new application. This consuming p...

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This paper presents the properties of the minimum mean cycle-canceling algorithm for solving linear programming models. Originally designed by Goldberg ...

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In this paper, we introduce a new variant of the vehicle routing problem with time windows (VRPTW) that arises in parcel delivery by postal services. In addi...

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We introduce iterative methods named TriCG and TriMR for solving symmetric quasi-definite systems based on the orthogonal tridiagonalization process proposed...

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Personnel scheduling aims to determine least-cost personnel schedules to meet the demand for employees in each period of a planning horizon. In this article,...

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We describe a Julia implementation of Mehrotra's predictor-corrector method for convex quadratic optimization that is entirely open source and generic in tha...

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Algorithm NCL is designed for general smooth optimization problems
    where first and second derivatives are available,
    including problems whose constrai...

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