Rapidly Convergent Algorithms for Nonsmooth Optimization.

Abstract

This research has led to new developments for solving nonlinear optimization problems involving functions that are not everywhere differentiable and/or are implicitly defined, such as those that arise from dual formulations of optimization models. A rapidly convergent, both in the theoretical and the practical sense, algorithm has been developed for the single variable case where generalized derivatives are available. It is being extended to the case where only function values are known. Some of the single variable results, including the concept of better than linear convergence, have been extended to the multivariable case. In order to solve efficiently the particular quadratic programming subproblems generated by the n-variable method a specialized QP algorithm has been developed. Additional keywords: Nondifferential programming; FORTRAN. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jul 14, 1985
Accession Number
ADA159168

Entities

People

  • R. Mifflin

Organizations

  • Washington State University

Tags

Communities of Interest

  • C4I

DTIC Thesaurus Topics

  • Air Force
  • Air Force Facilities
  • Algorithms
  • Computer Programming
  • Convergence
  • Direction Finding
  • Mathematical Programming
  • Nonlinear Programming
  • Operations Research
  • Optimization
  • Parallel Computing
  • Parallel Processing
  • Quadratic Programming
  • Scientific Research
  • Universities

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