KYHTQT.

Scheduling Production of High Economic Values Crops in Plant Factory

Năm XB 2023 Tạp chí / Hội thảo Lecture Notes in Networks and Systems Volume 847 LNNS Đơn vị NT&TT DOI / Link https://doi.org/10.1007/978-3-031-49529-8_32 ↗

Tác giả

Tóm tắt

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.

Tài liệu tham khảo

[1] Anpo, M.: Plant factory using artificial light: adapting to environmental disruption and clues to agricultural innovation. Elsevier Science (2018)

[2] Van Delden, S.H.: Current status and future challenges in implementing and upscaling vertical farming systems. Nat. Food 2(12), 944–956 (2021)

[3] Goto, E.: Plant production in a closed plant factory with artificial lighting, ActaHorticulturae 956, 37–49 (2012)

[4] Cetegen, S.A.: Optimal design of controlled environment agricultural systems under market uncertainty. Comput. Chem. Eng. 149, 107285 (2021)

[5] Huang, K.-L.: Plant factory crop scheduling considering volume, yield changes and multi-period harvests using Lagrangian relaxation. Biosys. Eng. 200, 328–337 (2020)

[6] Santini, A.: The crop growth planning problem in vertical farming. Eur. J. Oper. Res. 294(1), 377–390 (2021)

[7] Schulman, B.: A production capacity investment decision-making tool for the indoor vertical farming industry. Smart Agric. Technol. 5, 100244 (2023)

[8] You, P.-S.: A computational approach for crop production of organic vegetables. Comput. Electron. Agric. 134, 33–42 (2017)

[9] Yang, C.-L.: Recursive heuristic scheduling method for multi-crop plant factory with solar panel roof. Comput. Electron. Agric. 165, 104941 (2019)

[10] dos Santos, L.M.R.: Crop rotation scheduling with adjacency constraints. Ann. Oper. Res. 190, 165–180 (2011)

Ghi chú

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