Abstract
In this paper, we apply a competitive coevolutionary approach using loosely coupled genetic algorithms to a distributed optimization of the Rosenbrock's function. The computational scheme is a coevolutionary system of agents with only local interaction among them, without any central synchronization. We use a recently developed coordination language called Manifold to implement our distributed optimization algorithm. We show that the distributed optimization algorithm implemented using Manifold outperforms the sequential optimization algorithm based on a standard genetic algorithm.
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Seredynski, F., Bouvry, P., Arbab, F. (1997). Parallel and distributed evolutionary computation with MANIFOLD. In: Malyshkin, V. (eds) Parallel Computing Technologies. PaCT 1997. Lecture Notes in Computer Science, vol 1277. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-63371-5_11
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DOI: https://doi.org/10.1007/3-540-63371-5_11
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