Relatively recent techniques for categorical simulations are based on multi-point statistical approaches where a training image is used to derive complex spa...

In Positron Emission Tomography (PET), deep crystals (>20 mm) must be used to enhance detection efficiency and increase overall scanner sensitivity. Howeve...

Global optimization problems are very hard to solve, especially when the nonlinear constraints are highly nonconvex, which can result in a large number of di...

In this paper we solve the discrete time mean-variance hedging problem when asset returns follow a multivariate autoregressive hidden Markov model. Time dep...

In this paper, we first present a review of statistical tools that can be used in asset management either to track financial indexes or to create synthetic o...

The bid construction problem (BCP) for combinatorial total truckload transportation service procurement auctions consists of determining one or several bids ...

We consider the problems of determining the metric dimension and the minimum cardinality of doubly resolving sets in \(n\)-cubes. Most heuristics develope...

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

In this study, the problem environment consists of two fast fashion retailing firms where one can obtain the other's selling data from an outside agent. The ...

Recently, two different copula-based approaches have been proposed to estimate the conditional quantile function of a variable \(Y\) with respect to a vect...

This paper analyzes the effects of geological heterogeneity representation in a producing reservoir, when different stochastic simulation methods are used, s...

For pattern-based simulation methods such as SIMPAT, filtersim, wavesim, ect, patterns are stored by scanning a training image with a sliding template. Dimen...

Given a complete directed graph \(G\) with weights on the vertices and on the arcs, a \(\theta\)-improper \(k\)-coloring of \(G\) is an assignment of...

The maximum \(k\)-colorable subgraph problem (\(k\)-MCSP) is to color as many vertices as possible with at most \(k\) colors, such that no two adjacent...

Clustering addresses the problem of finding homogeneous and well-separated subsets, called clusters, from a set of given data points. In addition to the poi...

The \(k\)-means is a benchmark algorithm used in cluster analysis. It belongs to the large category of heuristics based on location-allocation steps that ...

The balanced clustering problem consists of partitioning a set of \(n\) objects into \(K\) equal-sized clusters as long as \(n\) is a multiple of `(K...

We propose the option realized variance as a new observable covariate that integrates high frequency option prices in the inference of option pricing models....

Security prices are important inputs for estimating credit risk models. Yet, to obtain an accurate firm-specific credit risk assessment, one needs a reliable...

In this paper we propose a new variant of the Variable Neighborhood Decomposition Search (VNDS) heuristic for solving global optimization problems and apply ...