The eccentric connectivity index of a connected graph \(G\) is the sum over all vertices \(v\) of the product \(d_G(v)e_G(v)\), where \(d_G(v)\) is ...

In this paper, we consider non-stationary response variables and covariates, where the marginal distributions and the associated copula may be time-dependent...

The eccentricity of a vertex \(v\) in a graph \(G\) is the maximum distance between \(v\) and any other vertex of \(G\). The diameter of a graph `(...

A graceful difference labeling (gdl for short) of a directed graph \(G\) with vertex set \(V\) is a bijection `(f:V\rightarrow{1,\ldots,\vert V\vert}...

Given a directed graph \(G=(V,A)\), capacity and cost functions on \(A\), a root \(r\), a subset \(T \subset V\) of terminals, and an integer \(k\)...

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

Generally, the semiclosed-form option pricing formula for complex financial models depends on unobservable factors such as stochastic volatility and jump int...

In this paper, we address a personalized multi-department multi-day shift scheduling problem with a multi-skill heterogeneous workforce where employees can b...

Vehicle routing problems (VRPs) are among the most studied problems in operations research. Nowadays, the leading exact algorithms for solving many classes o...

In this paper, we present an online reinforcement learning algorithm, called Renewal Monte Carlo (RMC), for infinite horizon Markov decision processes with ...

Clustering is an automated and powerful technique for data analysis. It aims to divide a given set of data points into clusters which are homogeneous and/o...

The vertex \(p\)-center problem consists in selecting \(p\) centers among a finite set of candidates and assigning a set of clients to them, with the aim...

Parrondo's paradox is extended to regime switching random walks in random environments. The paradoxical behavior of the resulting random walk is explained...

The survivorship bias in credit risk modeling is the bias that results in parameter estimates when the survival of a company is ignored. We study the statist...

Within state-of-the-art optimization solvers such as IBM--CPLEX the ability to solve both convex and nonconvex Mixed-Integer Quadratic Programming (MIQP) pro...

For over a decade, stochastic optimization has emerged as a framework that is capable of generating a life-of-mine production schedule that increases ne...

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...