AMOSA with Analytical Tuning Parameters for Heterogeneous Computing Scheduling Problem-Reference-Cited by-同舟云学术

AMOSA with Analytical Tuning Parameters for Heterogeneous Computing Scheduling Problem

Published:2016-12-10 Issue: Volume: Page:701-711
ISSN:1860-949X
Container-title:Nature-Inspired Design of Hybrid Intelligent Systems
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Author:

Fraire Huacuja Héctor Joaquín,Frausto-Solís Juan,Terán-Villanueva J. David,Soto-Monterrubio José Carlos,González Barbosa J. Javier,Castilla-Valdez Guadalupe

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-47054-2_46

Reference17 articles.

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3. G. Magklis, G. Semeraro, D. H. Albonesi, S. G. Dropsho, S. Dwarkadas and M. L. Scott, “Dynamic frequency and voltage scaling for a multiple-clock-domain microprocessor,” Micro, IEEE, vol. 23, no. 6, pp. 62-68, 2003.

4. S. Bandyopadhyay, S. Saha, U. Maulik and K. Deb, “A simulated annealing-based multiobjective optimization algorithm: AMOSA},,” IEEE Transactions on Evolutionary Computation, vol. 12, no. 3, pp. 269-283, 2008.

5. J. Frausto-Solís, H. Sanvicente-Sánchez and F. Imperial-Valenzuela, “ANDYMARK: an analytical method to establish dynamically the length of the markov chain in simulated annealing for the satisfiability problem,” in Simulated Evolution and Learning, Springer, 2006, pp. 269-276.

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