George B. Dantzig and systems optimization

Authors:
Philip E. Gill;Walter Murray;Michael A. Saunders;John A. Tomlin;Margaret H. Wright
Affiliations:
Department of Mathematics, University of California, San Diego, La Jolla, CA 92093, United States;Department of Management Science and Engineering, Stanford University, Stanford, CA 94305, United States;Department of Management Science and Engineering, Stanford University, Stanford, CA 94305, United States;Yahoo! Research, Sunnyvale, CA 94089, United States;Computer Science Department, Courant Institute of Mathematical Sciences, New York University, New York, NY 10012, United States
Venue:
Discrete Optimization
Year:
2008

Citing 10
Cited 0

A new polynomial-time algorithm for linear programming

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

Mathematical Programming: Series A and B
Distribution of mathematical software via electronic mail

Communications of the ACM
An analysis of an available set of linear programming test problems

Computers and Operations Research
Interior point algorithms: theory and analysis

Interior point algorithms: theory and analysis
Solving Real-World Linear Programs: A Decade and More of Progress

Operations Research
Smoothed analysis of algorithms: Why the simplex algorithm usually takes polynomial time

Journal of the ACM (JACM)
George B. Dantzig: a legendary life in mathematical programming

Mathematical Programming: Series A and B
George B. Dantzig: Operations Research Icon

Operations Research
Maintaining a sparse inverse in the simplex method

IBM Journal of Research and Development

Quantified Score

Hi-index	0.00

Visualization

Abstract

We pay homage to George B. Dantzig by describing a less well-known part of his legacy-his early and dedicated championship of the importance of systems optimization in solving complex real-world problems.