Abstract
Spatial distribution of individuals in evolutionary search combined with agent-based interactions within a population formed of multiple societies can induce new powerful models for complex optimization problems. The proposed search model relies on the distribution of individuals in a spatial environment, the collaboration and coevolution of individuals able to act like agents. Asynchronous search process is facilitated through a gradual propagation of genetic material into the population. Recombination and mutation processes are guided by the population geometrical structure. The proposed model specifies three strategies for recombination corresponding to three subpopulations (societies of agents). Each individual (agent) in the population has the goal of optimizing its fitness and is able to communicate and select a mate for recombination. Numerical results indicate the performance of the proposed distributed asynchronous search model.
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Chira, C., Gog, A., Dumitrescu, D. (2009). Distribution, Collaboration and Coevolution in Asynchronous Search. In: Corchado, J.M., RodrÃguez, S., Llinas, J., Molina, J.M. (eds) International Symposium on Distributed Computing and Artificial Intelligence 2008 (DCAI 2008). Advances in Soft Computing, vol 50. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85863-8_71
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DOI: https://doi.org/10.1007/978-3-540-85863-8_71
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