Abstract
Considering the energy conservation and emissions reduction, carbon-efficient scheduling becomes more and more important to the manufacturing industry. This paper addresses the multi-objective distributed permutation flow-shop scheduling problem (DPFSP) with makespan and total carbon emissions criteria (MODPFSP-Makespan-Carbon). Some properties to the problem are provided, and a competitive memetic algorithm (CMA) is proposed. In the CMA, some search operators compete with each other, and a local search procedure is embedded to enhance the exploitation. Meanwhile, the factory assignment adjustment is used for each job, and the speed adjustment is used to further improve the non-dominated solutions. To investigate the effect of parameter setting, full-factorial experiments are carried out. Moreover, numerical comparisons are given to demonstrate the effectiveness of the CMA.
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Acknowledgement
This research is supported by the National Key Basic Research and Development Program of China (No. 2013CB329503) and the National Science Fund for Distinguished Young Scholars of China (No. 61525304).
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Deng, J., Wang, L., Wu, C., Wang, J., Zheng, X. (2016). A Competitive Memetic Algorithm for Carbon-Efficient Scheduling of Distributed Flow-Shop. In: Huang, DS., Bevilacqua, V., Premaratne, P. (eds) Intelligent Computing Theories and Application. ICIC 2016. Lecture Notes in Computer Science(), vol 9771. Springer, Cham. https://doi.org/10.1007/978-3-319-42291-6_48
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DOI: https://doi.org/10.1007/978-3-319-42291-6_48
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