Abstract
In this paper, a hybrid quantum-inspired evolution algorithm (HQEA) is proposed to solve the blocking flow shop scheduling problem (BFSP) with the objectives of makespan and carbon-efficient. First, depending on the characteristics of quantum, we provided a feasible coding and decoding method for HQEA. Then, a mechanism intended to update the quantum probability matrix. Meanwhile, new individuals are generated through the quantum probability matrix and have a specified probability of cataclysm. In addition, some local search operators are utilized to improve the non-dominated solutions. Finally, the effectiveness of HQEA in solving the BFSP is demonstrated by experiments and comparisons.
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Acknowledgements
This research is partially supported by the National Science Foundation of China (51665025), the Applied Basic Research Foundation of Yunnan Province (2015FB136), and the National Natural Science Fund for Distinguished Young Scholars of China (61525304).
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Yao, YJ., Qian, B., Hu, R., Wang, L., Xiang, FH. (2018). Carbon-Efficient Scheduling of Blocking Flow Shop by Hybrid Quantum-Inspired Evolution Algorithm. In: Huang, DS., Bevilacqua, V., Premaratne, P., Gupta, P. (eds) Intelligent Computing Theories and Application. ICIC 2018. Lecture Notes in Computer Science(), vol 10954. Springer, Cham. https://doi.org/10.1007/978-3-319-95930-6_61
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