MIXED CONVEX AND NON-CONVEX PROGRAMMING.

Abstract

In the paper an algorithm is described for solving mixed convex-nonconvex programming problems of the form: minimize f sub o(x, y) subject to f sub j(x, y) < or = 0, j = 1, ..., k, where x is an n-vector and y is an m-vector and, in addition to some other mild conditions, for each y, f sub j(x, y), j = 0, ..., k, is a convex function of x. The algorithm consists of an efficient scan of the 'non-convex' (y) space in conjunction with convex programming methods in the 'convex' (x) space to find the global minimum of f sub o with a reasonable amount of computational effort. The algorithm will be practicable only when the number m of 'non-convex' variables is moderate, say m < or = 5.

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1970
Accession Number
AD0702461

Entities

People

  • Herman Otto Hartley
  • L. R. Lamotte
  • M. D. George

Organizations

  • Texas A&M University

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Applied Mathematics
  • Computer Programming
  • Convex Programming
  • Evolutionary Algorithms
  • Heuristic Methods
  • Interdisciplinary Science
  • Mathematical Programming
  • Mathematics
  • Nonconvex Programming
  • Operations Research

Fields of Study

  • Mathematics

Readers

  • Analytical Mechanics
  • Operations Research

Technology Areas

  • Space