Comparison of some conjugate direction procedures for function minimization

DOI10.1016/0016-0032(69)90253-1zbMath0228.90040OpenAlexW2093234862MaRDI QIDQ2549991

Harold W. Sorenson

Publication date: 1969

Published in: Journal of the Franklin Institute (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0016-0032(69)90253-1

Mathematics Subject Classification ID

Nonlinear programming (90C30)

Related Items (16)

Conjugate gradient algorithms in nonlinear structural analysis problems ⋮ A constraint-space conjugate gradient method for function minimization and optimal control problems† ⋮ A generalized direct search acceptable-point technique for use with descent-type multivariate algorithms ⋮ Simulating comparisons of different computing algorithms fitting zero-inflated Poisson models for zero abundant counts ⋮ Computational experience with conjugate gradient algorithms ⋮ On the Preconditioned Delayed Weighted Gradient Method ⋮ Efficient generalized conjugate gradient algorithms. I: Theory ⋮ Practical convergence conditions for unconstrained optimization ⋮ Convergence conditions for restarted conjugate gradient methods with inaccurate line searches ⋮ Nonlinear conjugate gradient methods with structured secant condition for nonlinear least squares problems ⋮ Approximation methods for the unconstrained optimization ⋮ Nonoptimal termination properties of quadratic interpolation univariate searches ⋮ A family of three-term conjugate gradient methods with sufficient descent property for unconstrained optimization ⋮ In favor of conjugate directions: a generalized acceptable-point algorithm for function minimization ⋮ A Rank Two Algorithm for Unconstrained Minimization ⋮ Unconstrained approach to the extremization of constrained functions

Cites Work

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• Properties of the conjugate-gradient and Davidon methods
• Non-Linear Programming—A Survey
• A Review of Minimization Techniques for Nonlinear Functions
• Some Algorithms for Minimizing a Function of Several Variables
• A Rapidly Convergent Descent Method for Minimization
• Function minimization by conjugate gradients
• An efficient method for finding the minimum of a function of several variables without calculating derivatives
• Nonlinear Programming: A Numerical Survey
• A Comparison of Several Current Optimization Methods, and the use of Transformations in Constrained Problems
• Davidon’s Method in Hilbert Space
• Methods of conjugate gradients for solving linear systems

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