Abstract
This work presents an application of Artificial Immune System (AIS) using Clonalg to the synthesis and optimization procedure of a Steel Catenary Riser (SCR) for floating oil production systems at deep and ultra-deep waters. The evaluation of the behavior of riser configurations, needed for the calculation of the fitness function in the optimization procedure by an evolutionary algorithm, requires a large number of time-consuming Finite Element analyses. Therefore, it is important to reduce the number of analyses; in this paper, the effectiveness of AIS for this purpose is assessed in this real-world industrial application. The results indicate that the AIS approach is more effective than Genetic Algorithms (GA), generating better solutions with smaller number of evaluations.
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Vieira, I.N., de Lima, B.S.L.P., Jacob, B.P. (2008). Optimization of Steel Catenary Risers for Offshore Oil Production Using Artificial Immune System. In: Bentley, P.J., Lee, D., Jung, S. (eds) Artificial Immune Systems. ICARIS 2008. Lecture Notes in Computer Science, vol 5132. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85072-4_23
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DOI: https://doi.org/10.1007/978-3-540-85072-4_23
Publisher Name: Springer, Berlin, Heidelberg
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