A Coevolutionary Approach to Cellular Automata-Based Task Scheduling

Author:

Oliveira Gina M. B.,Vidica Paulo M.

Publisher

Springer Berlin Heidelberg

Reference14 articles.

1. Goldberg, D.E.: Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley (1989)

2. Hillis, D.: Co-evolving parasites improves simulated evolution as an optimization procedure. Physica D 42(1-3), 228–234 (1991)

3. Wolfram, S.: Universality and complexity in cellular automata. Physica D 10, 1–35 (1984)

4. Seredynski, F.: Evolving cellular automata-based algorithms for multiprocessor scheduling. In: Zomaya, A., Ercal, F. (eds.) Solutions to Parallel and Distributed Computing Problems: Lessons from Biological Sciences, pp. 179–207 (2001)

5. Seredynski, F., Zomaya, A.Y.: Sequential and parallel cellular automata-based scheduling algorithms. IEEE Trans. Parallel Distrib. Syst. 13(10), 1009–1023 (2002)

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