Optimal ballast scheme design for cargo ships using an improved genetic algorithm. (25th February 2010)

• Record Type: Journal Article
• Authors: Chen, Jing; Lin, Yan; Huo, Jun Zhou; Zhang, Ming Xia; , Zhuo Shang Ji
• Is Part Of: International journal of innovative computing and applications. Volume 2:Number 2(2009)
• Page Start: 133
• Page End: 139
• Publication Date: 2010-02-25
• Subjects: ship design -- ship loading -- loading design -- innovative computing -- multi-objective optimisation -- combinational optimisation -- genetic algorithms -- GAs -- longitudinal strength -- stability -- ballast design -- cargo ships -- mathematical modelling -- dynamic adjustment -- tanker loading -- double hull tankers; Evolutionary computation -- Periodicals; Neural networks (Computer science) -- Periodicals; Genetic programming (Computer science) -- Periodicals; Biologically-inspired computing -- Periodicals; Swarm intelligence -- Periodicals; Quantum computers -- Periodicals; 006.3
• Languages: English
• ISSNs: 1751-648X

Abstract

Loading design is a key stage in ships' design process, and directly affects ships' stability, strength, and attitude at sea. The problem of loading design is a multi-objective combinatorial optimisation problem with multiple nonlinear constraints. In this paper, based on the complex technical requirements of ships' loading design, a mathematical model was constructed, taking the overall longitudinal strength and the intact stability performances as objectives, and the limits of ship's attitude, stability and strength, etc. as constraints. A strategy of tanks being fully-loaded-first was adopted and the corresponding improved genetic algorithm was presented where a novel heuristic dynamic adjusting rule was proposed to dynamically adjust the normalising coefficients of the non-commensurable objectives. Finally, a real case study on the loading design of a 50, 000 DWT double hull product tanker was conducted to illustrate the effectiveness of the proposed method.