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Research on intelligent design method of ship multi-deck compartment layout based on improved taboo search genetic algorithm

Citation

Wang, Y-L and Wu, Z-P and Guan, G and Li, K and Chai, S-H, Research on intelligent design method of ship multi-deck compartment layout based on improved taboo search genetic algorithm, Ocean Engineering, 225 Article 108823. ISSN 0029-8018 (2021) [Refereed Article]

Copyright Statement

Copyright 2021 Elsevier Ltd

DOI: doi:10.1016/j.oceaneng.2021.108823

Abstract

This paper presents an improved taboo search genetic algorithm (ITSGA) for intelligent design of ship multi-deck compartment layout (SMCL). The optimization of ship multi-deck residential compartment layout belongs to the combinatorial optimization problem with various performance constraints which needs to consider the layout of function cabins, deck passages and stairways between decks and so on. In this paper, the optimization model for SMCL is established, which include the layout area model, the relative location model, the absolute location model and the ergonomic model. ITSGA is proposed to improve the local search ability of genetic algorithm (GA) by introducing the neighborhood transformation criterion and Taboo criterion of Taboo search algorithm into GA. Then a new coding method is given according to the characteristics of ship cabins layout problem to avoid the damage to the cabin sequence caused by crossover and mutation operations in GA. During the layout process, the energy method is firstly used to determine the deck layer of various cabins to be arranged, and then the position of deck passages, cabins, and stairways between upper and lower decks are carried out by nested ITSGA. Finally, the results of numerical simulation experiments demonstrate the feasibility and effectiveness of the established method.

Item Details

Item Type:Refereed Article
Keywords:ship compartment layout, multi-deck, intelligent design, optimization model, taboo search algorithm, genetic algorithm
Research Division:Engineering
Research Group:Maritime engineering
Research Field:Naval architecture
Objective Division:Education and Training
Objective Group:Learner and learning
Objective Field:Higher education
UTAS Author:Wang, Y-L (Associate Professor Yunlong Wang)
UTAS Author:Chai, S-H (Professor Shuhong Chai)
ID Code:143353
Year Published:2021
Web of Science® Times Cited:10
Deposited By:NC Maritime Engineering and Hydrodynamics
Deposited On:2021-03-12
Last Modified:2021-06-25
Downloads:0

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