Practical methods of optimization; (2nd ed.)
Practical methods of optimization; (2nd ed.)
On combining feasibility, descent and superlinear convergence in inequality constrained optimization
Mathematical Programming: Series A and B
On multivariate Lagrange interpolation
Mathematics of Computation
Recent progress in unconstrained nonlinear optimization without derivatives
Mathematical Programming: Series A and B - Special issue: papers from ismp97, the 16th international symposium on mathematical programming, Lausanne EPFL
Basic Linear Algebra Subprograms for Fortran Usage
ACM Transactions on Mathematical Software (TOMS)
Trust-region methods
Lancelot: A FORTRAN Package for Large-Scale Nonlinear Optimization (Release A)
Lancelot: A FORTRAN Package for Large-Scale Nonlinear Optimization (Release A)
Test Examples for Nonlinear Programming Codes
Test Examples for Nonlinear Programming Codes
Numerical Methods for Unconstrained Optimization and Nonlinear Equations (Classics in Applied Mathematics, 16)
Controlled non-uniform random generation of decomposable structures
Theoretical Computer Science
Translation model adaptation by resampling
WMT '10 Proceedings of the Joint Fifth Workshop on Statistical Machine Translation and MetricsMATR
Constructing composite search directions with parameters in quadratic interpolation models
Journal of Global Optimization
Self-Correcting Geometry in Model-Based Algorithms for Derivative-Free Unconstrained Optimization
SIAM Journal on Optimization
WMT '11 Proceedings of the Sixth Workshop on Statistical Machine Translation
Mixing multiple translation models in statistical machine translation
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 1
Kriya - The SFU system for translation task at WMT-12
WMT '12 Proceedings of the Seventh Workshop on Statistical Machine Translation
A derivative-free algorithm for linearly constrained optimization problems
Computational Optimization and Applications
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This paper presents an algorithmic extension of Powell's UOBYQA algorithm (Unconstrained Optimization BY Quadratical Approximation). We start by summarizing the original algorithm of Powell and by presenting it in a more comprehensible form. Thereafter, we report comparative numerical results between UOBYQA, DFO and a parallel, constrained extension of UOBYQA that will be called in the paper CONDOR (COnstrained, Non-linear, Direct, parallel Optimization using trust Region method for high-computing load function). The experimental results are very encouraging and validate the approach. They open wide possibilities in the field of noisy and high-computing-load objective functions optimization (from 2min to several days) like, for instance, industrial shape optimization based on computation fluid dynamic codes or partial differential equations solvers. Finally, we present a new, easily comprehensible and fully stand-alone implementation in C++ of the parallel algorithm.