Parallel cross-entropy optimization

Gareth Evans, Jonathan Keith, Dirk Kroese

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

16 Citations (Scopus)

Abstract

The Cross-Entropy (CE) method is a modem and effective optimization method well suited to parallel implementations. There is a vast array of problems today, some of which are highly complex and can take weeks or even longer to solve using current optimization techniques. This paper presents a general method for designing parallel CE algorithms for Multiple Instruction Multiple Data (MIMD) distributed memory machines using the Message Passing Interface (MPI) library routines. We provide examples of its performance for two well-known test-cases: the (discrete) Max-Cut problem and (continuous) Rosenbrock problem. Speedup factors and a comparison to sequential CE methods are reported.
Original languageEnglish
Title of host publicationProceedings of the 2007 Winter Simulation Conference
EditorsShane Henderson, Ming-hua Hsieh
Place of PublicationUSA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages2196 - 2202
Number of pages7
ISBN (Print)9781424413058
DOIs
Publication statusPublished - 2007
Externally publishedYes
EventWinter Simulation Conference 2007 - Washington, United States of America
Duration: 9 Dec 200712 Dec 2007

Conference

ConferenceWinter Simulation Conference 2007
Abbreviated titleWSC 2007
CountryUnited States of America
CityWashington
Period9/12/0712/12/07

Cite this

Evans, G., Keith, J., & Kroese, D. (2007). Parallel cross-entropy optimization. In S. Henderson, & M. Hsieh (Eds.), Proceedings of the 2007 Winter Simulation Conference (pp. 2196 - 2202). IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/WSC.2007.4419854