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Multi-objective optimization of high speed vehicle-passenger catamaran by genetic algorithm Cover

Multi-objective optimization of high speed vehicle-passenger catamaran by genetic algorithm

Open Access
|Jan 2012

Abstract

Real ship structural design problems are usually characterized by presence of many conflicting objectives. Simultaneously, a complete definition of the optimum structural design requires a formulation of size-topology-shape-material optimization task unifying the optimization problems from the four areas and giving an effective solution of the problem. Any significant progress towards solving the problem has not been obtained so far. An objective of the present paper was to develop an evolutionary algorithm for multiobjective optimization of the structural elements of large spatial sections of ships. Selected elements of the multi-criteria optimization theory have been presented in detail. Methods for solution of the multi-criteria optimization problems have been discussed with the focus on the evolutionary optimization algorithms. In the paper an evolutionary algorithm where selection takes place based on the aggregated objective function combined with domination attributes as well as distance to the asymptotic solution, is proposed and applied to solve the problem of optimizing structural elements with respect to their weight and surface area for a high - speed vehicle-passenger catamaran structure, with taking into account several design variables such as plate thickness, scantlings of longitudinal stiffeners and transverse frames, and spacing between longitudinal and transversal members. Details of the computational models were kept at the level typical for conceptual design stage. Scantlings were analyzed by using the selected classification society rules. The results of numerical experiments with the use of the developed algorithm are presented. They show that the proposed genetic algorithm may be considered an efficient tool for multi-objective optimization of ship structures.

The paper has been published in the three parts: Part I: Theoretical background on evolutionary multi-objective optimization, Part II: Computational simulations, and Part III: Analysis of the results.

DOI: https://doi.org/10.2478/v10012-011-0020-0 | Journal eISSN: 2083-7429 | Journal ISSN: 1233-2585
Language: English
Page range: 3 - 13
Published on: Jan 6, 2012
Published by: Gdansk University of Technology
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2012 Zbigniew Sekulski, published by Gdansk University of Technology
This work is licensed under the Creative Commons License.

Volume 18 (2011): Issue 4 (October 2011)