Abstract
The paper proposes using genetic algorithms - based learning classifier system (CS) to solve multiprocessor scheduling problem. After initial mapping tasks of a parallel program into processors of a parallel system, the agents associated with tasks perform migration to find an allocation providing the minimal execution time of the program. Decisions concerning agents' actions are produced by the CS, upon a presentation by an agent information about its current situation. Results of experimental study of the scheduler are presented. © 2000 Springer-Verlag Berlin Heidelberg.
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CITATION STYLE
Nowacki, J. P., Pycka, G., & Seredyński, F. (2000). Multiprocessor scheduling with support by genetic algorithms - Based learning classifier system. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1800 LNCS, pp. 604–611). Springer Verlag. https://doi.org/10.1007/3-540-45591-4_82
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