Industrial Engineering and Management Systems

Korean Institute of Industrial Engineers (대한산업공학회)
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Hybrid Genetic Algorithms for Solving Reentrant Flow-Shop Scheduling with Time Windows

  • Chamnanlor, Chettha (Department of Industrial Engineering, Faculty of Engineering, Khon Kaen University) ;
  • Sethanan, Kanchana (Department of Industrial Engineering, Faculty of Engineering, Khon Kaen University) ;
  • Chien, Chen-Fu (Department of Industrial Engineering and Engineering Management, National Tsing Hua University) ;
  • Gen, Mitsuo (Department of Industrial Engineering and Engineering Management, National Tsing Hua University, Fuzzy Logic System Institute)
  • Received : 2013.01.21
  • Accepted : 2013.10.11
  • Published : 2013.12.31
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Abstract

The semiconductor industry has grown rapidly, and subsequently production planning problems have raised many important research issues. The reentrant flow-shop (RFS) scheduling problem with time windows constraint for harddisk devices (HDD) manufacturing is one such problem of the expanded semiconductor industry. The RFS scheduling problem with the objective of minimizing the makespan of jobs is considered. Meeting this objective is directly related to maximizing the system throughput which is the most important of HDD industry requirements. Moreover, most manufacturing systems have to handle the quality of semiconductor material. The time windows constraint in the manufacturing system must then be considered. In this paper, we propose a hybrid genetic algorithm (HGA) for improving chromosomes/offspring by checking and repairing time window constraint and improving offspring by left-shift routines as a local search algorithm to solve effectively the RFS scheduling problem with time windows constraint. Numerical experiments on several problems show that the proposed HGA approach has higher search capability to improve quality of solutions.

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References

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