Parametric design and multiobjective optimization of containerships

Priftis, Alexandros and Papanikolaou, Apostolos and Plessas, Timoleon (2016) Parametric design and multiobjective optimization of containerships. Journal of Ship Production and Design, 32 (3). pp. 1-14. ISSN 2158-2866

[thumbnail of Priftis-etal-JSPD-2016-Parametric-design-and-multi-objective-optimization]
Text (Priftis-etal-JSPD-2016-Parametric-design-and-multi-objective-optimization)
Accepted Author Manuscript
License: Unspecified

Download (773kB)| Preview


    The introduction of the energy efficiency design index (EEDI) and ballast water treatment regulations by the International Maritime Organization, the fluctuation of fuel price levels, along with the continuous endeavor of the shipping industry for economic growth and profits has led the shipbuilding industry to explore new and cost-efficient designs for various types of merchant ships. In this respect, proper use of modern computer-aided design/computer-aided engineering systems (CAD/CAE) extends the design space, while generating competitive designs with innovative features in short lead time. The present article deals with the parametric design and optimization of containerships. The developed methodology, which is based on the CAESES/Friendship-Framework software system, is demonstrated by the conceptual design and multiobjective optimization of a midsized, 6500-TEU containership. The methodology includes a complete parametric model of the ship’s external and internal geometry and the development and coding of all models necessary for the determination of the design constraints and the design efficiency indicators, which are used for the evaluation of parametrically generated designs. Such indicators defining the objective functions of a multiobjective optimization problem are herein the EEDI, the required freight rate, the ship’s zero ballast container box capacity, and the ratio of the above to below deck number of containers.The set-up multiobjective optimization problem is solved by use of the genetic algorithms, and clear Pareto fronts are generated. Identified optimal design proves very competitive compared with the standard containership designs in the market.

    ORCID iDs

    Priftis, Alexandros ORCID logoORCID:, Papanikolaou, Apostolos and Plessas, Timoleon;