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- Walter Murray

Discipline name
D-index
D-index (Discipline H-index) only includes papers and citation values for an examined
discipline in contrast to General H-index which accounts for publications across all
disciplines.
Citations
Publications
World Ranking
National Ranking

Mathematics
D-index
44
Citations
16,497
115
World Ranking
1055
National Ranking
495

1918 - Fellow of the Royal Society of Canada

- Mathematical optimization
- Algebra
- Algorithm

Walter Murray focuses on Mathematical optimization, Nonlinear programming, Constrained optimization, Factorization and Applied mathematics. Walter Murray combines subjects such as Algorithm and Hessian matrix with his study of Mathematical optimization. Walter Murray has researched Nonlinear programming in several fields, including Function and Environmental engineering.

His research integrates issues of Quadratic programming and Augmented Lagrangian method in his study of Constrained optimization. His study in Factorization is interdisciplinary in nature, drawing from both Matrix decomposition, Matrix, Incomplete LU factorization and Cholesky decomposition. His Applied mathematics research is multidisciplinary, relying on both Linear equation, Iterative method, Linear programming, Simplex algorithm and Interior point method.

- Methods for modifying matrix factorizations. (505 citations)
- Algorithms for the Solution of the Nonlinear Least-Squares Problem (440 citations)
- Numerical linear algebra and optimization (357 citations)

Walter Murray mostly deals with Mathematical optimization, Nonlinear programming, Quadratic programming, Constrained optimization and Sequential quadratic programming. The study incorporates disciplines such as Function, Hessian matrix and Nonlinear system in addition to Mathematical optimization. His Nonlinear programming research incorporates themes from Software, Linear programming, Iterative method, Algorithm and Sequence.

In the subject of general Quadratic programming, his work in Quadratically constrained quadratic program is often linked to Scale, thereby combining diverse domains of study. His research in Constrained optimization intersects with topics in Penalty method, Factorization, Logarithm, Computation and Numerical analysis. His work deals with themes such as Matrix decomposition and Orthogonality, which intersect with Factorization.

- Mathematical optimization (66.67%)
- Nonlinear programming (40.74%)
- Quadratic programming (34.57%)

- Mathematical optimization (66.67%)
- Nonlinear programming (40.74%)
- Constrained optimization (32.10%)

His primary scientific interests are in Mathematical optimization, Nonlinear programming, Constrained optimization, Nonlinear system and Augmented Lagrangian method. His work in the fields of Mathematical optimization, such as Heuristic, intersects with other areas such as AC power. The concepts of his Nonlinear programming study are interwoven with issues in Algorithm, Discrete optimization and Investment decisions.

The various areas that Walter Murray examines in his Algorithm study include Axiom and Investment. His Constrained optimization research is multidisciplinary, incorporating elements of Local optimum and Quadratic programming, Sequential quadratic programming. His studies deal with areas such as Function and Fortran as well as Quadratic programming.

- An algorithm for nonlinear optimization problems with binary variables (98 citations)
- User's Guide for SNOPT Version 7.5: Software for Large-Scale Nonlinear Programming (65 citations)
- Methods for modifying matrix factorizations. (57 citations)

- Mathematical optimization
- Algebra
- Algorithm

His main research concerns Mathematical optimization, Nonlinear programming, Constrained optimization, Algorithm and Pure mathematics. His studies in Mathematical optimization integrate themes in fields like Function, Cardinality and Nonlinear system. Walter Murray interconnects Local optimum, Bilevel optimization, Quadratic programming, Set and Decomposition in the investigation of issues within Nonlinear programming.

His Constrained optimization study incorporates themes from Sequence, Metric space and Heuristic. His Algorithm study integrates concerns from other disciplines, such as Stochastic programming and Bounded function. His study on Pure mathematics is mostly dedicated to connecting different topics, such as Matrix.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

SNOPT: An SQP Algorithm for Large-Scale Constrained Optimization

Philip E. Gill;Walter Murray;Michael A. Saunders.

Siam Review **(2005)**

4515 Citations

SNOPT: An SQP Algorithm for Large-Scale Constrained Optimization

Philip E. Gill;Walter Murray;Michael A. Saunders.

Siam Review **(2005)**

4515 Citations

SNOPT: An SQP Algorithm for Large-Scale Constrained Optimization

Philip E. Gill;Walter Murray;Michael A. Saunders.

Siam Journal on Optimization **(2002)**

1947 Citations

Numerical Linear Algebra and Optimization

Philip E. Gill;Walter Murray;Margaret H. Wright.

**(2021)**

850 Citations

Numerical Linear Algebra and Optimization

Philip E. Gill;Walter Murray;Margaret H. Wright.

**(2021)**

850 Citations

Methods for modifying matrix factorizations.

Phillip E. Gill;Gene H. Golub;Walter A. Murray;Michael A. Saunders.

Mathematics of Computation **(1972)**

838 Citations

Methods for modifying matrix factorizations.

Phillip E. Gill;Gene H. Golub;Walter A. Murray;Michael A. Saunders.

Mathematics of Computation **(1972)**

838 Citations

Algorithms for the Solution of the Nonlinear Least-Squares Problem

Philip E. Gill;Walter Murray.

SIAM Journal on Numerical Analysis **(1978)**

752 Citations

Algorithms for the Solution of the Nonlinear Least-Squares Problem

Philip E. Gill;Walter Murray.

SIAM Journal on Numerical Analysis **(1978)**

752 Citations

On projected Newton barrier methods for linear programming and an equivalence to Karmarkar's projective method

Philip E. Gill;Walter Murray;Michael A. Saunders;J. A. Tomlin.

Mathematical Programming **(1986)**

647 Citations

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