Year: 2004
Type: report
Abstract: . The DIRECT algorithm is a deterministic sampling method for bound constrained Lipschitz continuous optimization. We prove a subsequential convergence result for the DIRECT algorithm that quantifies some of the convergence observations in the literature. Our results apply to several variations on the original method, including one that will handle general constraints. We use techniques from nonsmooth analysis, and our framework is based on recent results for the MADS sampling algorithms.
Authors: D. Finkel, C. T. Kelley
Language: English
Subfield: Numerical Analysis
Field: Mathematics
Domain: Physical Sciences
Open Access status: green
Awards: ITR/AP: Collaborative Research: Sampling Methods for Optimization and Control of Subsurface Contamination, Nonlinear Equations and Optimization, Volume-based Analysis of 6-month Infant Brain MRI for Autism Biomarker Identification and Early Diagnosis, Continued Development of Infant Brain Analysis Tools, Scientific Computing Research Environments for the Mathematical Sciences (SCREMS)
OpenAlex ID: W32104792