Taylor Series Models in Deterministic Global Optimization
by
R. Baker Kearfott
University of Louisiana at Lafayette

Deterministic global optimization requires a global search with rejection of subregions. To reject a subregion, bounds on the range of the constraints and objective function can be used. Although sometimes effective, simple interval arithmetic sometimes gives impractically large bounds on the ranges. However, Taylor models as developed by Berz et al show promise in this context. We thoroughly investigate such Taylor models within the GlobSol deterministic global optimization software environment.

http://interval.usl.edu/preprints/AD-2000_extended_abstract.ps

Date received: January 11, 2000