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A Comparative Study of Large-Scale Nonlinear Optimization Algorithms

H.Y. Benson (hyurttan***at***princeton.edu)
D.F. Shanno (shanno***at***rutcor.rutgers.edu)
R.J. Vanderbei (rvdb***at***princeton.edu)

Abstract: In recent years, much work has been done on implementing a variety of algorithms in nonlinear programming software. In this paper, we analyze the performance of several state-of-the-art optimization codes on large-scale nonlinear optimization problems. Extensive numerical results are presented on different classes of problems, and features of each code that make it efficient or inefficient for each class are examined.

Keywords: interior-point methods, large-scale optimization, nonlinear programming

Category 1: Nonlinear Optimization (Constrained Nonlinear Optimization )

Category 2: Nonlinear Optimization (Quadratic Programming )

Category 3: Nonlinear Optimization (Unconstrained Optimization )

Citation: ORFE 01-04, Department of Operations Research and Financial Engineering, Princeton University, Princeton, NJ 08544, December 2001.

Download: [PDF]

Entry Submitted: 12/05/2001
Entry Accepted: 12/05/2001
Entry Last Modified: 12/05/2001

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