DocumentCode :
442034
Title :
Research on 3MO-based genetic algorithm for solving order planning
Author :
Zhang, Tao ; Zhang, Yue-jie ; Wang, Meng-Guang
Author_Institution :
Sch. of Inf. Manage. & Eng., Shanghai Univ. of Finance & Econ., China
Volume :
6
fYear :
2005
fDate :
18-21 Aug. 2005
Firstpage :
3650
Abstract :
This paper proposes a mixed integer-programming model for order planning of iron-steel enterprise. Because this problem is a kind NP-hard problem and the size of this problem is bigger, the genetic algorithm based on repeatable natural scale code and 3-mutation operator is presented to solve the model. For ensuring the quality of copy strategy of the genetic algorithm, this paper develops an improving selection function for copying. Finally, this paper uses the order planning of Shanghai Baoshan iron-steel enterprise as an example to test the model and the algorithm. The numerical analysis shows that the model comes up to the production process, the solutions obtained by this algorithm are superior to those obtained by the human-machine system. So, the model and the algorithm are valid.
Keywords :
computational complexity; genetic algorithms; integer programming; order processing; production planning; 3-mutation operator; NP-hard problem; copy strategy; genetic algorithm; human-machine system; iron-steel enterprise; mixed integer-programming model; natural scale code; numerical analysis; order planning; production planning process; selection function; Capacity planning; Finance; Genetic algorithms; Information management; Linear programming; Mathematical model; Process planning; Production planning; Steel; Testing; 3-mutation operator (3MO); Order planning (OP); genetic algorithm (GA); mixed integer programming; production process;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
Conference_Location :
Guangzhou, China
Print_ISBN :
0-7803-9091-1
Type :
conf
DOI :
10.1109/ICMLC.2005.1527575
Filename :
1527575
Link To Document :
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