An improved quantum genetic algorithm based on MAGTD for dynamic FJSP

Original Research
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Abstract

For the purpose of solving the dynamic flexible job-shop scheduling problem, this paper establishes the mathematical model to minimize the makespan and stability value, an improved double chains quantum genetic algorithm was proposed. Firstly, it is proposed that the method of double chains structure coding including machine allocation chain and process chain. Secondly, it is proposed that non- dominated sorting based on the crowding distance selection strategy. Thirdly, the most satisfying solution is obtained through the multi-attribute grey target decision model. Finally, the novel method is applied to the Brandimarte example and a dynamic simulation, the result of comparing with other classical algorithms verifies its effectiveness.

Keywords

Flexible job-shop scheduling Dynamic scheduling strategy Double chains quantum genetic algorithm Multi-attribute grey target decision 
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Notes

Acknowledgements

This work is financially supported by the National Natural Science Foundation, China (No. 51579024), Liaoning Provincial Natural Science Foundation of China (No. 201602131), Dr scientific research fund of Liaoning Province (No. 201601244), Liaoning Provincial Social Science Planning Foundation of China (No. L16BGL008) and Dalian Social Science Foundation of China (2016dlskyb104).

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Copyright information

© Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  1. 1.Institute of SoftwareDalian Jiaotong UniversityDalianChina

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