What is he best known for?
The fields of study he is best known for:
- 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.
His most cited work include:
- 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)
What are the main themes of his work throughout his whole career to date?
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.
He most often published in these fields:
- Mathematical optimization (66.67%)
- Nonlinear programming (40.74%)
- Quadratic programming (34.57%)
What were the highlights of his more recent work (between 2004-2015)?
- Mathematical optimization (66.67%)
- Nonlinear programming (40.74%)
- Constrained optimization (32.10%)
In recent papers he was focusing on the following fields of study:
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.
Between 2004 and 2015, his most popular works were:
- 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)
In his most recent research, the most cited papers focused on:
- 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.
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