World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
37
Citations
12181
World Ranking
2415
National Ranking
1012

Engineering and Technology

D-Index
37
Citations
12180
World Ranking
8232
National Ranking
2265

Research.com Recognitions

  • 2005 - Fellow of the Institute for Operations Research and the Management Sciences (INFORMS)

Overview

David F. Shanno was affiliated with Rutgers, The State University of New Jersey in the United States. Their research primarily focused on mathematics, with a specialization in numerical analysis and computational aspects of mathematics.

Their main fields of study included:

  • Mathematics

They contributed to several subfields such as:

  • Numerical Analysis
  • Computational Theory and Mathematics
  • Computational Mechanics
  • Mathematical Physics

The topics of Shanno's research centered on algorithmic and optimization methods. Specific areas of work were:

  • Advanced Optimization Algorithms Research
  • Matrix Theory and Algorithms
  • Sparse and Compressive Sensing Techniques
  • Numerical Methods in Inverse Problems
  • Iterative Methods for Nonlinear Equations

Among the recent publications attributed to Shanno's research collaborations were:

  • "Regularized Step Directions in Nonlinear Conjugate Gradient Methods," published in 2021 in arXiv (Cornell University)
  • "Regularized step directions in nonlinear conjugate gradient methods," published in 2024 in Mathematical Programming Computation

Frequent co-authors who contributed to these works included Cassidy K. Buhler and Hande Y. Benson.

The main venues that published their research were:

  • arXiv (Cornell University)
  • Mathematical Programming Computation

David F. Shanno was recognized by peers and professional organizations, having been named a Fellow of the Institute for Operations Research and the Management Sciences (INFORMS) in 2005.

Best Publications

  • Conditioning of Quasi-Newton Methods for Function Minimization

    D. F. Shanno

  • An Interior-Point Algorithm for Nonconvex Nonlinear Programming

    Robert J. Vanderbei;David F. Shanno

  • Conjugate Gradient Methods with Inexact Searches

    David F. Shanno

  • Option Pricing when the Variance Is Changing

    Herb Johnson;David Shanno

  • ON IMPLEMENTING MEHROTRA'S PREDICTOR-CORRECTOR INTERIOR-POINT METHOD FOR LINEAR PROGRAMMING*

    Irvin J. Lustig;Roy E. Marsten;David F. Shanno

  • Computational experience with a primal-dual interior point method for linear programming

    Irvin J. Lustig;Roy E. Marsten;David F. Shanno

  • Remark on “Algorithm 500: Minimization of Unconstrained Multivariate Functions [E4]”

    D. F. Shanno;K. H. Phua

  • Feature Article—Interior Point Methods for Linear Programming: Computational State of the Art

    Irvin J. Lustig;Roy E. Marsten;David F. Shanno

  • Matrix conditioning and nonlinear optimization

    David F. Shanno;Kang-Hoh Phua

  • An Implementation of a Primal-Dual Interior Point Method for Linear Programming

    Kevin A. McShane;Clyde L. Monma;David F. Shanno

  • Very large-scale linear programming: a case study in combining interior point and simplex methods

    Robert E. Bixby;John W. Gregory;Irvin J. Lustig;Roy E. Marsten

  • An example of numerical nonconvergence of a variable-metric method

    D. F. Shanno

  • Algorithm 500: Minimization of Unconstrained Multivariate Functions [E4]

    D. F. Shanno;K. H. Phua

  • On the Convergence of a New Conjugate Gradient Algorithm

    D. F. Shanno

  • Optimal conditioning of quasi-Newton methods

    D. F. Shanno;P. C. Kettler

  • Interior-Point Methods for Nonconvex Nonlinear Programming: Filter Methods and Merit Functions

    Hande Y. Benson;Robert J. Vanderbei;David F. Shanno

  • Interior-point methods for nonconvex nonlinear programming: Orderings and higher-order methods

    David F. Shanno;Robert J. Vanderbei

  • Interior Point Methods for Linear Programming: Just Call Newton, Lagrange, and Fiacco and McCormick!

    Roy Marsten;Radhika Subramanian;Matthew Saltzman;Irvin Lustig

  • Higher-Order Predictor-Corrector Interior Point Methods with Application to Quadratic Objectives

    Tamra J. Carpenter;Irvin J. Lusting;John M. Mulvey;David F. Shanno

  • Further Development of a Primal-Dual Interior Point Method

    In Chan Choi;Clyde L. Monma;David F. Shanno

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