Application of Genetic Algorithms to the Synthesis of Riser Configurations

Abstract

The purpose of this work is to describe the application of Genetic Algorithms in the search of the best configuration of catenary riser systems in deep waters. Particularly, an optimization methodology based on genetic algorithms is implemented on a computer program, in order to seek an optimum geometric configuration for a steel catenary riser in a lazy-wave configuration. This problem is characterized by a very large space of possible solutions; the use of traditional methods is an exhaustive work, since there is a large number of variables and parameters that define this type of system. Genetic algorithms are more robust than the more commonly used optimization techniques. They use random choice as a tool to guide a search toward regions of the search space with likely improvements. Some differences such as the coding of the parameter set, the search from a population of points, the use of objective functions and randomized operators are factors that contribute to the robustness of a genetic algorithm and result in advantages over traditional techniques. The implemented methodology has as baseline one or more criteria established by the experience of the offshore engineer. The implementation of an intelligent methodology oriented specifically to the optimization and synthesis of riser configurations will not only facilitate the work of manipulating a huge mass of data, but also assure the best alternative between all the possible ones, searching in a much larger space of possible solutions than classical methods.