DocumentCode :
2974855
Title :
Research on shipbuilding schedule based on genetic algorithm
Author :
Zhao, Duanyang ; Gao, Jiaquan ; Xu, Qingxiang
Author_Institution :
Zhijiang Coll., Zhejiang Univ. of Technol., Hangzhou, China
fYear :
2009
fDate :
22-24 June 2009
Firstpage :
1619
Lastpage :
1624
Abstract :
The overall arrangement in shipbuilding project is a strategic problem, whose purpose is to obtain an optimal scheme with the shortest days for construction and the best economic benefits. Here a multiobjective model of shipbuilding schedule is proposed, and a new genetic algorithm based on a vector group encoding method in order to effectively solve it. The shipbuilding scheduling problem with minimizing the maximum completion time among all the jobs and minimizing the total earliness/tardiness penalty of all the jobs is a parallel machine scheduling one, but it is different from other parallel machine scheduling problems with the following characteristics. Firstly, the machines are non-identical; secondly, the sort of job processed on every machine can be restricted. For our proposed algorithm, its encoding method is simple and can effectively reflect the virtual scheduling policy, which can vividly reflect the numbers and sequences of these processed jobs on every machine, and enables the individuals generated by crossover and mutation to satisfy process constraint. Numerical results show that our proposed algorithm is efficient, and outperforms the common genetic algorithm.
Keywords :
genetic algorithms; scheduling; shipbuilding industry; earliness penalty; economic benefits; genetic algorithm; parallel machine scheduling; shipbuilding project; shipbuilding scheduling problem; strategic problem; tardiness penalty; vector group encoding method; virtual scheduling policy; Automation; Encoding; Genetic algorithms; Genetic mutations; Parallel machines; Scheduling algorithm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information and Automation, 2009. ICIA '09. International Conference on
Conference_Location :
Zhuhai, Macau
Print_ISBN :
978-1-4244-3607-1
Electronic_ISBN :
978-1-4244-3608-8
Type :
conf
DOI :
10.1109/ICINFA.2009.5205176
Filename :
5205176
Link To Document :
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