Title
Multi-scale optimization
Document Type
Article
Date of Original Version
12-1-2004
Abstract
Global optimization problems with so-called 'rough' or rugged objective function landscapes are studied. These problems often have many, many stationary points and show considerable differences between small and large-scale geometry. A novel multi-scale global optimization algorithm for solving 'rough' objective functions, based on the alternate use of terrain methods and new funneling algorithms, is presented. Small-scale information is gathered using a terrain optimization methodology while funneling algorithms are used to guide the overall optimization calculations and to make 'large' moves within the feasible region. A molecular modeling example is used to clearly illustrate that the proposed methodology is capable of finding a global minimum without calculating all stationary points and can lead to significant reductions in computational work. © 2004 Elsevier B.V. All rights reserved.
Publication Title, e.g., Journal
Computer Aided Chemical Engineering
Volume
18
Issue
C
Citation/Publisher Attribution
Lucia, Angelo, and Peter A. DiMaggio. "Multi-scale optimization." Computer Aided Chemical Engineering 18, C (2004): 1093-1098. doi: 10.1016/S1570-7946(04)80248-7.