Abstract
This paper presents a problem-solving framework based on robust evolutionary search in GRID computing environment. Our problem-solving environment called virtual innovative laboratory performs simulator programs in parallel and optimize their input parameters employing a competent evolutionary algorithm with gene analysis. The objective of our project is to replace a part of human designer’s try-and-error processes by a parallel and robust evolutionary search on GRID computing systems.
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Munetomo, M., Munawar, A., Akama, K. (2007). A Framework of GRID Problem-Solving Environment Employing Robust Evolutionary Search. In: Moreno Díaz, R., Pichler, F., Quesada Arencibia, A. (eds) Computer Aided Systems Theory – EUROCAST 2007. EUROCAST 2007. Lecture Notes in Computer Science, vol 4739. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75867-9_60
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DOI: https://doi.org/10.1007/978-3-540-75867-9_60
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-75866-2
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