Title: Pareto optimisation of grillage system with multi-objectives

Authors: Yunyoung Kim, Byeong-Il Kim, Joo-Shin Park

Addresses: Department of Naval Architecture and Ocean Engineering, Mokpo National Maritime University, Jukyo-dong 571, Mokpo-si, Jeollanam-do, 530-701, Korea. ' Department of Naval Architecture and Ocean Engineering, Mokpo National Maritime University, Jukyo-dong 571, Mokpo-si, Jeollanam-do, 530-701, Korea. ' Marine Research Institute, Samsung Heavy Industries Co. Ltd., Jangpyung-dong 530, Geoje-si, Kyeong Nam, Korea

Abstract: Many real-world design problems involve simultaneous optimisation of multiple objectives. The considered grillage design is a multi-objective optimisation problem since there are two objective functions, namely: the volume design and the cost design. Thus, the solution of this optimisation problem requires specialised method suitable for multi-objective problems. In this article, a multi-objective design optimisation using real-coded genetic algorithm is proposed for the Pareto-optimality of grillage system. The objective functions in the optimisation problem measure the design sensitivities in grillage system. The non-linear constrained multi-objective optimisation is very important from the point of view of practical problem solving. Therefore, the real-coded genetic algorithm with multiple genetic operators is proposed to find the optimum grillage system without handling any of the penalty functions. Direct strength calculation defined from the class rules of DNV was applied for structural design of grillage system. The hybrid method (real-coded genetic algorithm including the non-dominated sorting and sharing approaches) performs a marvellous explorability in finding a diverse set of solutions and in converging near the true Pareto-optimal set. The results obtained are very encouraging since they show that we can produce an important portion of the Pareto-front at a very low computational time frame.

Keywords: grillage systems; Pareto optimal set; real-coded genetic algorithms; RGA; multi-objective optimisation; design optimisation; optimal design; design sensitivities.

DOI: 10.1504/IJMIC.2009.029266

International Journal of Modelling, Identification and Control, 2009 Vol.8 No.3, pp.213 - 221

Available online: 17 Nov 2009 *

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