Trends in wireless networks are proceeding toward increasingly dense deployments, supporting resilient interconnection for applications that carry ever highe...

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

Blackbox optimization problems are often contaminated with numerical noise, and direct search methods such as the Mesh Adaptive Direct Search (MADS) algorit...

The authors investigate the complexity needed in the structure of the scenario trees to maximize energy production in a rolling-horizon framework. Three comp...

We present a new derivative-free trust-region (DFTR) algorithm to solve general nonlinear constrained problems with the use of an augmented Lagrangian m...

This paper presents a new high-order, non-stationary sequential simulation approach, aiming to deal with the typically complex, curvilinear structures and hi...

This paper examines the issue of price and advertising coordination in bilateral monopolies from a dynamic perspective. Its main objectives are to design i...

We study derivative-free constrained optimization problems and propose a trust-region method that builds linear or quadratic models around the best feasible ...

We propose a dynamic program coupled with finite elements for valuing two-dimensional American-style options. To speed-up our procedure, we use parallel comp...

Airline crew scheduling is typically performed in two steps : crew pairing followed by crew assignment. The crew pairing problem (CPP) finds a set of pairing...

We consider within the framework of Mean Field Games theory a dynamic discrete choice model with an advertiser, where a large number of minor agents (e.g., c...

We consider a dynamic collective choice problem where a large number of players are cooperatively choosing between multiple destinations while being influenc...

In this paper we consider an interactive communication system with two users, who sequentially observe two correlated sources, and send the quantized observa...

An augmented Lagrangian (AL) can convert a constrained optimization problem into a sequence of simpler (e.g., unconstrained) problems, which are then usual...

NLP.py is a programming environment to model continuous optimization problems and to design computational methods in the high-level and powerful Python l...

We study a rich production-routing problem with time windows arising at a catering services company. The production part consists of assembling the meals to ...

The geometric-arithmetic index \(GA\) of a graph \(G\) is the sum of ratios, over all edges of \(G\), of the geometric mean to the arithmetic mean of t...

In the present paper, we prove lower and upper bounds for each of the ratios \(GA/\delta\), \(GA/\overline{d}\) and \(\Delta\), in terms of the order `...

In the present paper, we compare the geometric-arithmetic index \(GA\) and the chromatic number \(\chi\) of a connected graph with given order. We prove,...

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