Optimization of FPSO spread mooring systems with a surrogate- assisted Differential Evolution algorithm
Palavras-chave:
mooring, FPSO, optimization, differential evolution, neural networksResumo
The design of mooring systems is a complex and time-consuming task that must be thoroughly
addressed in every Oil & Gas upstream project. Up to now, the task is performed mostly based on the expertise
and engineering judgment of the analysts, with little to no optimization ever pursued. This article presents a method
that employs the well-known ε-Constrained Differential Evolution algorithm to design the mooring system and
makes use of Artificial Neural Networks to evaluate its performance, thus eliminating the constraints imposed by
the limited capabilities of the human mind and providing feasible systems with reduced costs.
