A Parallel Interval Computation Model for Global Optimization with Automatic Load Balancing

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Title A Parallel Interval Computation Model for Global Optimization with Automatic Load Balancing
Author Wu, Yong; Kumar, Arun
Journal Name Journal of Computer Science and Technology
Year Published 2012
Place of publication United States
Publisher Springer New York LLC
Abstract In this paper, we propose a decentralized parallel computation model for global optimization using interval analysis. The model is adaptive to any number of processors and the workload is automatically and evenly distributed among all processors by alternative message passing. The problems received by each processor are processed based on their local dominance properties, which avoids unnecessary interval evaluations. Further, the problem is treated as a whole at the beginning of computation so that no initial decomposition scheme is required. Numerical experiments indicate that the model works well and is stable with different number of parallel processors, distributes the load evenly among the processors, and provides an impressive speedup, especially when the problem is time-consuming to solve.
Peer Reviewed Yes
Published Yes
Alternative URI http://dx.doi.org/10.1007/s11390-012-1260-x
Copyright Statement Copyright 2012 Springer Boston. This is an electronic version of an article published in Journal of Computer Science and Technology, July 2012, Volume 27, Issue 4, pp 744-753. Journal of Computer Science and Technology is available online at: http://link.springer.com// with the open URL of your article.
Volume 27
Issue Number 4
Page from 744
Page to 753
ISSN 1000-9000
Date Accessioned 2012-06-28
Language en_US
Research Centre Institute for Integrated and Intelligent Systems
Faculty Griffith Business School
Subject Distributed Computing; Optimisation
URI http://hdl.handle.net/10072/47145
Publication Type Journal Articles (Refereed Article)
Publication Type Code c1

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