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

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

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 `...

This paper presents a numerical investigation of the non-hierarchical formulation of Analytical Target Cascading (ATC) for coordinating distributed multidisc...

This paper proposes a bilevel formulation for a coupled planning and operation problem of an advanced microgrid. The proposed model, recast as a mathematical...

We describe a collection of linear systems generated during the iterations of an interior-point method for convex quadratic optimization. As the iteration...

This work describes the application of a direct search method to the optimization of problems of real industrial interest, namely three new material scien...

This paper considers a family of cutting planes, recently developed for mixed 0-1 polynomial programs and shows that they define facets for the maximum edge-...

A new algorithm for the optimal stope design problem is proposed. It is based on a previous methodology developed by Bai et al. (2013a) where a cylindrical ...

Decentralized stochastic control refers to the multi-stage optimization of a dynamical system by multiple controllers that have access to different informati...

In decentralized control systems with linear dynamics, quadratic cost, and Gaussian disturbance (also called decentralized LQG systems) linear control strate...

Various constrained problem formulations for the optimization of an electro-thermal wing anti-icing system in both running-wet and evaporative regimes are pr...

In many large engineering design problems, it is not computationally feasible or realistic to store Jacobians or Hessians explicitly. Matrix-free implementat...

Aircraft sizing, route network design, demand estimation and allocation of aircraft to routes are different facets of the air transportation optimization pro...

Blackbox optimization deals with situations in which the objective function and constraints are typically computed by launching a time-consuming computer ...

A preconditioned variant of the Golub and Kahan (1965) bidiagonalization process recently proposed by Arioli (2013) and Arioli and Orban (2013) allows us to ...

We propose a generalization of the limited-memory Cholesky factorization of Lin and Moré (1999) to the symmetric indefinite case with special interest in sym...

Symmetric quasi-definite systems may be interpreted as regularized linear least-squares problem in appropriate metrics and arise from applications such as re...

We describe the most recent evolution of our constrained and unconstrained testing environment and its accompanying SIF decoder. Code-named SIFDecode and CU...

Projected Krylov methods are full-space formulations of Krylov methods that take place in a nullspace. Provided projections into the nullspace can be compute...