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AD685796

Publication Date 1968
Personal Author McCormick, G. P.
Page Count 12
Abstract An algorithm for solving the optimization problem: minimize f(x) subject to x sub j > or = 0, j = 1,..., n is presented. The algorithm is a simple modification of Cauchy's steepest descent method. The main idea is to move from any point x to the k power along a feasible piece-wise linear path defined by the constraint set and gradient f(x to the k power), taking x to the (k+1) power to be the first local minimizing point along that path. Convergence to a constrained stationary point is proved. (Author)
Keywords
  • Nonlinear programming
  • Simplex method
  • Saddle point method
  • Convergence
  • Optimization
  • Algorithms
  • Reprints
NTIS Subject Category
  • 72E - Operations Research
Corporate Authors Research Analysis Corp Mclean VA
Supplemental Notes Revision of Rept. dated Nov 67.
Document Type Journal Article
Title Note Technical paper.
NTIS Issue Number 196912
Contract Number
  • DAHC19-69-C-0017
Anti-Zig-Zagging by Bending.
Anti-Zig-Zagging by Bending.
AD685796

  • Nonlinear programming
  • Simplex method
  • Saddle point method
  • Convergence
  • Optimization
  • Algorithms
  • Reprints
  • 72E - Operations Research
  • DAHC19-69-C-0017
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