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Chinese Journal of Management Science ›› 2009, Vol. 17 ›› Issue (5): 68-74.

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Two-Stage Genetic Algorithm for SM-CC Production Scheduling

LI Tie-ke, SU Zhi-xiong   

  1. School of Economics and Management, University of Science and Technology Beijing, Beijing 100083, China
  • Received:2008-12-05 Revised:2009-09-06 Online:2009-10-31 Published:2009-10-31

Abstract: Steelmaking-continuous casting production process can be abstracted as a hybrid flow-shop.AO-1 mixed-integer linear programming model is established for this scheduling problem. In this model,no dead time inside the same cast at the last stage is treated as equality constraint,and graded penalty method is used to balance the sojourn times. Based on Benders'decomposition,a two-stage genetic algorithm combined GA and LP is proposed. In the algorithm design,a new chromosome encoding is used to represent the charge assignment and processing sequence solution,and genetic operations are given for this coding scheme. In the first stage,a high quality population by minimizing the weighted sum of overlapping time is found. And in the second stage the linear programming model to guide the iteration process is used. Finally,the result of simulation experiment with practical production data indicates that it is an efficient algorithm for this production scheduling problem.

Key words: production scheduling, steelmaking-continuous casting, genetic algorithm, mathematical programming

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