Accession Number:

ADA445031

Title:

Filter Pattern Search Algorithms for Mixed Variable Constrained Optimization Problems

Descriptive Note:

Corporate Author:

AIR FORCE INST OF TECH WRIGHT-PATTERSON AFB OH

Report Date:

2004-06-21

Pagination or Media Count:

32.0

Abstract:

A new class of algorithms for solving nonlinearly constrained mixed variable optimization problems is presented. This class combines and extends the Audet-Dennis Generalized Pattern Search GPS algorithms for bound constrained mixed variable optimization, and their GPS-filter algorithms for general nonlinear constraints. In generalizing existing algorithms, new theoretical convergence results are presented that reduce seamlessly to existing results for more specific classes of problems. While no local continuity or smoothness assumptions are required to apply the algorithm, a hierarchy of theoretical convergence results based on the Clarke calculus is given, in which local smoothness dictate what can be proved about certain limit points generated by the algorithm. To demonstrate the usefulness of the algorithm, the algorithm is applied to the design of a load-bearing thermal insulation system. We believe this is the first algorithm with provable convergence results to directly target this class of problems.

Subject Categories:

  • Numerical Mathematics
  • Operations Research

Distribution Statement:

APPROVED FOR PUBLIC RELEASE