Dominique Orban

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The initial release of CUTE, a widely used testing environment for optimization software, was described by Bongartz, et al. [1995]. A new version, now known as CUTEr, is presented. Features include reorganisation of the environment to allow simultaneous multi-platform installation, new tools for, and interfaces to, optimization packages, and a considerably(More)
We describe the design of version 1.0 of GALAHAD, a library of Fortran 90 packages for large-scale nonlinear optimization. The library particularly addresses quadratic programming problems, containing both interior point and active set algorithms, as well as tools for preprocessing problems prior to solution. It also contains an updated version of the(More)
An interior-point method for nonlinear programming is presented. It enjoys the flexibility of switching between a line search method that computes steps by factoring the primal-dual equations and a trust region method that uses a conjugate gradient iteration. Steps computed by direct factorization are always tried first, but if they are deemed ineffective,(More)
A new primal-dual algorithm is proposed for the minimization of non-convex objective functions subject to general inequality and linear equality constraints. The method uses a primal-dual trust-region model to ensure descent on a suitable merit function. Convergence is proved to second-order critical points from arbitrary starting points. Numerical results(More)
Abstract. We examine the sequence of local minimizers of the log-barrier function for a nonlinear program near a solution at which second-order sufficient conditions and the Mangasarian-Fromovitz constraint qualifications are satisfied, but the active constraint gradients are not necessarily linearly independent. When a strict complementarity condition is(More)
A mixed interior/exterior-point method for nonlinear programming is described, that handles constraints by an `1-penalty function. A suitable decomposition of the penalty terms and embedding of the problem into a higherdimensional setting leads to an equivalent, surprisingly regular, reformulation as a smooth penalty problem only involving inequality(More)
Interior-point methods feature prominently among numerical methods for inequalityconstrained optimization problems, and involve the need to solve a sequence of linear systems that typically become increasingly ill-conditioned with the iterations. To solve these systems, whose original form has a nonsymmetric 3×3 block structure, it is common practice to(More)
We describe the most recent evolution of our constrained and unconstrained testing environment and its accompanying SIF decoder. Code-named SIFDecode and CUTEst, these updated versions feature dynamic memory allocation, a modern thread-safe Fortran modular design, a new Matlab interface and a revised installation procedure integrated with GALAHAD. 1(More)
We examine symbolic tools associated with two modeling systems for mathematical programming, which can be used to automatically detect the presence or absence of convexity and concavity in the objective and constraint functions, as well as convexity of the feasible set in some cases. The coconut solver system Schichl (2004b) focuses on nonlinear global(More)
Projected Krylov methods are full-space formulations of Krylov methods that take place in a nullspace. Provided projections into the nullspace can be computed accurately, those methods only require products between an operator and vectors lying in the nullspace. We provide systematic principles for obtaining the projected form of any well-defined Krylov(More)