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...

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....

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

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...

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

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...

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 ...

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 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...

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

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

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 ...

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

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

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

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

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

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

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