Abstract
In this paper, single-machine scheduling with carbon emission index is studied. The objective function is to minimize the sum of total flow time and carbon emission. Firstly, the problem is shown to be NP-hard by Turing reduction. Then mathematical programming (MP) model is established. A pseudo-time algorithm based on dynamic programming (DPA) is proposed for small scale. And a Bird Swarm Algorithm (BSA) is proposed to compete with DPA. In addition, simulation experiments are used to compare the proposed algorithms. DPA is shown to be more efficient for small scale problem, and BSA is better for large scale problem.
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Acknowledgement
This research is partially supported by the National Science Foundation of China (51665025), and the Applied Basic Research Foundation of Yunnan Province (2015FB136).
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Zhang, HL., Qian, B., Sun, ZX., Hu, R., Liu, B., Guo, N. (2018). Single-Machine Green Scheduling to Minimize Total Flow Time and Carbon Emission. 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_67
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DOI: https://doi.org/10.1007/978-3-319-95930-6_67
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