J
Jorge J. Moré
Researcher at Argonne National Laboratory
Publications - 86
Citations - 24264
Jorge J. Moré is an academic researcher from Argonne National Laboratory. The author has contributed to research in topics: Optimization problem & Nonlinear system. The author has an hindex of 48, co-authored 86 publications receiving 22010 citations. Previous affiliations of Jorge J. Moré include Cornell University & Rice University.
Papers
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Global smoothing and continuation for large-scale molecular optimization
Jorge J. Moré,Zhijun Wu +1 more
TL;DR: It is shown that continuation techniques based on global smoothing are applicable to these molecular optimization problems, and the issues that must be resolved in the solution of large-scale molecular optimize problems are outlined.
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Optimization and geophysical inverse problems
J. Barhen,James G. Berryman,Liliana Borcea,John E. Dennis,C. de Groot-Hedlin,F. Gilbert,P. Gill,Matthias Heinkenschloss,Lane R. Johnson,T. McEvilly,Jorge J. Moré,Gregory A. Newman,D. Oldenburg,P. Parker,B. Porto,M. Sen,Virginia Torczon,Donald W. Vasco,N.B. Woodward +18 more
TL;DR: In this article, the authors present a discussion of methods for solving geophysical inverse problems with an emphasis upon newer approaches that have not yet become prominent in geophysics, and the main results are brought together in a final summary and conclusions section.
ReportDOI
Global methods for nonlinear complementarity problems
TL;DR: This work forms the nonlinear complementarity problem as a bound-constrained nonlinear least squares problem, and algorithms based on this formulation are applicable to general non linear complementarity problems, and each iteration only requires the solution of systems of linear equations.
Journal ArticleDOI
Towards the universal nuclear energy density functional
Mario Stoitsov,Mario Stoitsov,Mario Stoitsov,Jorge J. Moré,Witold Nazarewicz,Witold Nazarewicz,Witold Nazarewicz,Junchen Pei,Junchen Pei,Jason Sarich,Nicolas Schunck,Nicolas Schunck,Andrzej Staszczak,Andrzej Staszczak,Andrzej Staszczak,Stefan M. Wild +15 more
TL;DR: The UNEDF SciDAC project as mentioned in this paper developed and optimized the energy density functional for atomic nuclei using state-of-the-art computational infrastructure, and the ultimate goal is to replace current phenomenological models of the nucleus with a well-founded microscopic theory with minimal uncertainties.
Proceedings ArticleDOI
Scalable Algorithms in Optimization: Computational Experiments
TL;DR: This work surveys techniques in the Toolkit for Advanced Optimization for developing scalable algorithms for mesh-based optimization problems on distributed architectures and shows that these techniques, together with mesh sequencing, can produce results that scale with mesh size.