Keywords: pipelines, route optimization, evolutionary algorithms, on-bottom stability, vortex-induced vibrations, induced fatigue.

Submarine pipelines have been extensively employed to convey oil or gas from offshore petroleum exploitation activities. One important stage of their design consists in the selection of the best route. Traditionally, this task has been manually performed by the engineer, by inspection of seabed bathymetry and available information regarding obstacles. However, it has already been recognized that the selection of a route with good performance and low cost must be formally described and treated as an optimization problem, where each candidate route is evaluated considering several constraints derived from bathymetry and sonography data (declivity; obstacles and regions that should be avoided; regions of interest that should be approached, etc.).

In this context, previous work has described initial steps in the development of a computational tool, based on evolutionary algorithms, for the optimization of submarine pipeline routes. Now, this work is focused on an enhanced version of the tool incorporating not only the minimization of route length, but also other objectives: minimizing the ballast weight required for hydrodynamic stability, and the free spans that could lead to fatigue generated by vortex-induced vibrations. Also, the efficiency of different evolutionary algorithms (genetic algorithm, artificial immune system and particle swarm optimization) are evaluated and compared.

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