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Bio‐inspired algorithms for the optimization of offshore oil production systems
Author(s) -
Vieira Ian Nascimento,
Lima Beatriz Souza Leite Pires,
Jacob Breno Pinheiro
Publication year - 2012
Publication title -
international journal for numerical methods in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.421
H-Index - 168
eISSN - 1097-0207
pISSN - 0029-5981
DOI - 10.1002/nme.4301
Subject(s) - particle swarm optimization , fitness function , meta optimization , genetic algorithm , mathematical optimization , multi swarm optimization , computer science , metaheuristic , algorithm , artificial immune system , multi objective optimization , function (biology) , swarm behaviour , nonlinear system , test functions for optimization , artificial intelligence , mathematics , physics , quantum mechanics , evolutionary biology , biology
SUMMARY This work describes the development, implementation, and assessment of enhanced variants of three different groups of bio‐inspired methodologies: genetic algorithms, particle swarm optimization, and artificial immune system. The algorithms are implemented on a computational tool for the synthesis and optimization of offshore oil production risers that connect a floating platform at the sea surface to the wellheads at the sea bottom. Optimization procedures using bio‐inspired algorithms for such real‐world engineering problems require the calculation of the objective function through a large number of time‐consuming finite element nonlinear dynamic analyses, for the evaluation of the structural behavior of each candidate configuration. Therefore, the performance of the algorithms may be measured by the smaller number of objective function evaluations associated to a given target fitness value. The results indicate that the artificial immune system approach, incorporating some enhancements presented in this work, is more effective than the genetic algorithms and particle swarm optimization methods, requiring a smaller number of evaluations to obtain better solutions. Copyright © 2012 John Wiley & Sons, Ltd.