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Applied Computational Intelligence and Soft Computing
Volume 2010 (2010), Article ID 781598, 14 pages
Research Article

Modeling and Evolutionary Optimization on Multilevel Production Scheduling: A Case Study

1School of Control & Computer Engineering, North China Electric Power University, Beijing 102206, China
2College of Engineering Science & Technology, Shanghai Ocean University, Shanghai 201306, China
3School of Economics & Management, Beihang University, Beijing 100083, China

Received 31 August 2009; Revised 27 February 2010; Accepted 16 April 2010

Academic Editor: Chuan-Kang Ting

Copyright © 2010 Ruifeng Shi et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Multilevel production scheduling problem is a typical combinatorial optimization problem in a manufacturing system, which is traditionally modeled as several hierarchical sublevel problems and optimized at each level, respectively. An integrated model, which can cope with the whole multilevel scheduling information simultaneously, is proposed in this paper, and a specific evolutionary algorithm is designed to solve the integrated model with a twin-screw coding strategy. In order to evaluate the performance of the new algorithm, a real 3-level production scheduling problem is employed for case study, and two typical metaheuristic algorithms, a genetic algorithm (GA) and a simulated annealing (SA), are also employed for comparison study. Experimental simulation results show that our proposed modeling and optimization method has outperformed the other ones.