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Binary quadratic programming (BQP) is a class of combinatorial optimization problems comprising binary variables, quadratic objective functions and linear/no...
référence BibTeXAdaptive simultaneous stochastic optimization of mining complexes: Where is the value coming from?
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 ...
référence BibTeXStochastic stope design optimization under grade uncertainty and dynamic development costs
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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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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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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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...
référence BibTeXMultiple streams with recurrence-based, counter-based, and splittable random number generators
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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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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Nous étudions une classe de jeux déterministes à horizon fini à deux joueurs à somme non nulle où les joueurs sont dotés de différents types de commandes....
référence BibTeXBlackbox optimization
The goal of the Encyclopedia of Optimization is to introduce the reader to a complete set of topics that sh...
référence BibTeXIntegrating learning and explicit model predictive control for unit commitment in microgrids
Dans cet article, nous adressons le problème de l’ordonnancement de l’arrêt/démarrage des génératrices dans un microréseau selon une approche visant à s’assu...
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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...
référence BibTeXDeep reinforcement learning for optimal stopping with application in financial engineering
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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A small polygon is a polygon of unit diameter. The maximal perimeter and the maximal width of a convex small polygon with n=2s
sides are unknown when ...
A small polygon is a polygon of unit diameter. The maximal perimeter of a convex equilateral small polygon with n=2s
vertices is not known when `(s ...
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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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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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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A small polygon is a polygon of unit diameter. The maximal perimeter and the maximal width of a convex small polygon with n=2s
vertices are not known ...
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≥7
. Finding the large...