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Optimum Design of the Power Yacht Based on Micro-Genetic Algorithm
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 Title & Authors
Optimum Design of the Power Yacht Based on Micro-Genetic Algorithm
Park, Joo-Shin; Kim, Yun-Young;
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The optimum design of power yacht belongs to the nonlinear constrained optimization problems. The determination of scantlings for the bow structure is a very important issue with in the whole structural design process. The derived design results are obtained by the use of real-coded micro-genetic algorithm including evaluation from Lloyd`s Register small craft guideline, so that the nominal limiting stress requirement can be satisfied. In this study, the minimum volume design of bow structure on the power yacht was carried out based on the finite element analysis. The target model for optimum design and local structural analysis is the bow structure of a power yacht. The volume of bow structure and the main dimensions of structural members are chosen as an objective function and design variable, respectively. During optimization procedure, finite element analysis was performed to determine the constraint parameters at each iteration step of the optimization loop. optimization results were compared with a pre-existing design and it was possible to reduce approximately 19 percents of the total steel volume of bow structure from the previous design for the power yacht.
real-coded micro-genetic algorithm;buckling;minimum volume design;
 Cited by
Optimum Design of the Power Yacht Based on Micro-Genetic Algorithm, Journal of Navigation and Port Research, 2009, 33, 9, 635  crossref(new windwow)
ANSYS User's Theory Manual V10.0 (2005), "Chapter four Introduction to Material Nonlinearities", ANSYS Inc

Dario, B. and Massimo, F. (2001), "Stress Distribution at Collapse for Fast Mono Hull Vessels", FAST, 2001 4th–6th 2001, Southhampton, UK, pp.153-161

Herrera, F., Lozano, M., and Verdegay, J.L. (1998), "Tackling real-coded genetic algorithms: operators and tools for behavioral analysis", Artificial Intelligence Review, Vol. 12, No. 4, pp.265-319 crossref(new window)

Kim, Y., Gotoh, K., and Toyosada, M. (2004), "Global cutting-path optimization considering the minimum heat effect with microgenetic algorithms", J. of Marine Science and Technology, Vol. 9, No. 2, pp.70-79 crossref(new window)

Kim, Y., Kim, K. S, and Park, J. W. (2006), "Midship Section Optimization of Hatchcoverless Container Ship based on Real-Coded Micro-Genetic Algorithm", Key Engineering Materials, Vol. 306-308, pp.529-534 crossref(new window)

Kirkpatrick, S., Gelatt, C.D., and Vecchi, M.P. (1983), "Optimization by Simulated Annealing", Science, 220, 4598, pp.671-680 crossref(new window)

Lloyd's Register (2003), "Rules and Regulations for the Classification of Special Service Craft", Part 6, 2003. Hull Construction in Steel

Michalewicz, Z. (1994), "Genetic Algorithms + Data Structures = Evolution Programs", extended edition, Springer-Verlag, New York

Michalewicz, Z. and Janikow, C.Z. (1991), "Handling constraints in genetic algorithms", Proceedings of the 4th International Conference on Genetic Algorithms, Morgan Kaufmann Publishers, pp.151-157

Sebastiani, L., Valdenazzi, F., Grossi, L. and Kapsenberg, G.K. (2001), "A Theoritical and Experimental Investigation of the Slamming Pressure on Fast Monohull Vessels", FAST, 4th– 6th 2001, Southhampton, UK, pp.109-116

Smith, C.S., Davidson, P.C., Chapman, J.C. and Dowling, P.J.(1988), "Strength and stiffness of ship's plating under in-plane compression and tension", RINA Transactions, 130

Wright, A.H. (1991), "Genetic algorithms for real parameter optimization", Foundations of Genetic Algorithms, First Workshop on the Foundations of Genetic Algorithms and Classifier Systems, G.J.E. Rawlins (Ed.), Morgan Kaufmann Publishers, pp. 205-218