Multi-Objective Optimization of Mooring Systems for Offshore Renewable Energy

This work is funded by the EPSRC (UK) grant for the United Kingdom Centre for Marine Energy Research (UKCMER) [grant number: EP/P008682/1].

[1]  Lars Johanning,et al.  Mooring line fatigue damage evaluation for floating marine energy converters: Field measurements and prediction , 2014 .

[2]  Lars Johanning,et al.  Mooring design approach for wave energy converters , 2006 .

[3]  Philipp R. Thies,et al.  Development of a Multi-Objective Genetic Algorithm for the Design of Offshore Renewable Energy Systems , 2017 .

[4]  Jason Jonkman,et al.  Definition of the Semisubmersible Floating System for Phase II of OC4 , 2014 .

[5]  Jaap Schijve,et al.  Fatigue of structures and materials , 2001 .

[6]  Jason E. Heath,et al.  Mooring and Foundation Module Framework for DTOcean Tool , 2015 .

[7]  Jon Hardwick,et al.  A comprehensive assessment of the applicability of available and proposed offshore mooring and foundation technologies and design tools for array applications , 2014 .

[8]  Consolación Gil,et al.  Optimization methods applied to renewable and sustainable energy: A review , 2011 .

[9]  R. O. Snell,et al.  Fatigue Curves for Polyester Moorings - A State-of-the-Art Review , 2000 .

[10]  R. K. Ursem.  Multi-objective Optimization using Evolutionary Algorithms , 2009 .

[11]  Dan Boneh,et al.  On genetic algorithms , 1995, COLT '95.

[12]  Lalit M. Patnaik,et al.  Genetic algorithms: a survey , 1994, Computer.

[13]  Tea Tusar,et al.  Visualization of Pareto Front Approximations in Evolutionary Multiobjective Optimization: A Critical Review and the Prosection Method , 2015, IEEE Transactions on Evolutionary Computation.

[14]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..