Toward a methodology for the optimal design of mooring systems for floating offshore platforms using evolutionary algorithms

This work presents the first steps toward the development of an innovative computational tool, based on evolutionary optimization methods, for the synthesis and optimization of spread-mooring configurations for floating production systems (FPS). The modeling of the optimization problem departs from the classical design approach that has led to symmetrically distributed lines. As the complexity of FPS has been increasing for recent applications, we consider asymmetric configurations where the mooring radii and azimuthal angles of the lines vary along the corners of the platform. This increases the number of design variables, leading to thousands of alternative geometric configurations whose structural behavior should be evaluated during the optimization process. Since each evaluation requires extensively time-consuming nonlinear analyses, this might introduce severe limitations for the optimization tool. In this context, the goal is to assess the performance of two of the most popular evolutionary algorithms—the particle swarm optimization (PSO) and the differential evolution (DE) methods, applied to a case study representative of actual deep-water FPS. The results open many roads for future developments, indicating that evolutionary algorithms (EAs) with fast convergence and ability to explore the search space may be further explored toward the development of an efficient mooring optimization strategy. © 2016, Sociedade Brasileira de Engenharia Naval.