We describe the implementation of RipQP, an interior-point algorithm for convex quadratic optimization. Our Julia implementation is open source, and accommo...

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...

The estimation of the structural model poses a major challenge as its underlying asset (the firm's asset value) is not directly observable. We extend the m...

Recently equal risk pricing, a framework for fair derivative pricing, was extended to consider dynamic risk measures. However, all current implementations ei...

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...

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

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

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

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

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...

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...

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...

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

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

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

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

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...

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

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

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...

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...

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

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...

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 ...

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

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

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 ...

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...

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...

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

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

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...

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...

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

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

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 `...

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...

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

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

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...

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

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

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

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

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 ...

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

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

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

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...

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...

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...

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

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

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

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...

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 ...

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 ...

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...

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

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...

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 ...

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

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

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

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...

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 ...

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

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

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

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

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

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

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

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

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...

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...

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...

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...

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...

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

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...

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

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,...

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