Abstract
Plant factories were designed to control environmental factors such as temperature, relative humidity, light, and carbon dioxide concentration to optimize growth conditions and enhance crop quality. Crop selection and scheduling are obligated to get a consistent harvest in the plant factory. This study uses a Mixed Integer Linear Programming (MILP) approach to model the crop scheduling problem in Plant Factory. The objective function is designed to determine the maximum revenue while taking into account the practical operating circumstances, including crop price per unit and time, crop family and lighting demand, the number of harvests, and number of growing racks. While the optimization potentially solved scheduling issues, the challenges in modifying many racks must be addressed to ensure practical feasibility. Therefore, this study improved the Heuristic Plant Factory Scheduler (HPFS) algorithm by incorporating Dynamic Programming (DP). The experimental results demonstrated that HPFS with DP accelerated computational performance and produced acceptable scheduling quality, mainly when the crop allocation space is enormous.
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Acknowledgement
This work has been supported by VNU University of Engineering and Technology under project number CN21.24.
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Dai, N.D., Long, P.C., Phung, TN., Pham, MT., Le Nguyen, K., Do, DD. (2023). Scheduling Production of High Economic Values Crops in Plant Factory. In: Nghia, P.T., Thai, V.D., Thuy, N.T., Son, L.H., Huynh, VN. (eds) Advances in Information and Communication Technology. ICTA 2023. Lecture Notes in Networks and Systems, vol 847. Springer, Cham. https://doi.org/10.1007/978-3-031-49529-8_32
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DOI: https://doi.org/10.1007/978-3-031-49529-8_32
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