Asynchronous parallel hybrid optimization combining DIRECT and GSS.
- SAS Institute Inc., NC
In this talk, we explore the benefits of hybrid optimization using parallel versions of DIRECT and asynchronous generating set search (GSS) for optimization. Both of these methods are derivative-free, making them useful for a variety of science and engineering problems. Our goal is to ideally find a global minimum, but practically to find a good local minimum in a small amount of time. DIRECT is a global search method that systematically divides the search space into ever-smaller rectangles, and GSS is a local search method. The combination of these method guarantees a good local minimum but is better than a purely local approach because it finds more global solutions. We compare the performance of hybrid and non-hybrid methods on a suite of standard global optimization test problems. Overall, the hybrid methods are more robust than the non-hybrid methods at the cost of more function evaluations. In terms of wall-clock time on a parallel system, the hybrid methods are actually less expensive due to nearly perfect parallel load balance and scaling.
- Research Organization:
- Sandia National Laboratories (SNL), Albuquerque, NM, and Livermore, CA (United States)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- AC04-94AL85000
- OSTI ID:
- 951520
- Report Number(s):
- SAND2008-6666C; TRN: US200912%%6
- Resource Relation:
- Conference: Proposed for presentation at the AMR08: Applied Mathematics Principal Investigator Meeting held October 14-17, 2008 in Argonne, IL.
- Country of Publication:
- United States
- Language:
- English
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