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- W2097492041 abstract "We propose a solution of the multiprocessor scheduling problem based on applying a relatively new metaheuristic called Generalized Extremal Optimization (GEO). GEO is inspired by a simple coevolutionary model known as Bak-Sneppen model. The model assumes existing of an ecosystem consisting of N species. Evolution in this model is driven by a process in which the weakest species in the ecosystem, together with its nearest neighbors is always forced to mutate. This process shows characteristic of a phenomenon called a punctuated equilibrium which is observed in evolutionary biology. We interpret the multiprocessor scheduling problem in terms of the Bak-Sneppen model and apply the GEO algorithm to solve the problem. We show that the proposed optimization technique is simple and yet outperforms both genetic algorithm (GA)-based and particle swarm optimization (PSO) algorithm-based approaches to the multiprocessor scheduling problem." @default.
- W2097492041 created "2016-06-24" @default.
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- W2097492041 date "2009-05-01" @default.
- W2097492041 modified "2023-09-27" @default.
- W2097492041 title "Solving multiprocessor scheduling problem with GEO metaheuristic" @default.
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- W2097492041 doi "https://doi.org/10.1109/ipdps.2009.5161114" @default.
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