Abstract
This paper addresses the problem of Load-balancing when Parallel Genetic Programming is employed. Although load-balancing techniques are regularly applied in parallel and distributed systems for reducing makespan, their impact on the performance of different structured Evolutionary Algorithms, and particularly in Genetic Programming, have been scarcely studied. This paper presents a preliminary study and simulation of some recently proposed load balancing techniques when applied to Parallel Genetic Programming, with conclusions that may be extended to any Parallel or Distributed Evolutionary Algorithm.
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Fernández de Vega, F., Abengózar Sánchez, J.G., Cotta, C. (2011). A Preliminary Analysis and Simulation of Load Balancing Techniques Applied to Parallel Genetic Programming. In: Cabestany, J., Rojas, I., Joya, G. (eds) Advances in Computational Intelligence. IWANN 2011. Lecture Notes in Computer Science, vol 6692. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21498-1_39
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DOI: https://doi.org/10.1007/978-3-642-21498-1_39
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-21497-4
Online ISBN: 978-3-642-21498-1
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