Abstract
This paper proposes a new mathematical model for predictive scheduling of perishable material transports with the aim of reducing losses of perishable goods. The model is particularly designed for allocation of potatoes from several farms to a nearby starch mill, which produces starch from a limited amount of potatoes each day. Scheduling should determine how much amount of potatoes be sent from which farm to the mill on each day. It is known that the quality of potatoes decreases over time and as a result less starch is produced. A model predictive control approach is proposed to maximize the production of starch. Simulation experiments indicate that predictive scheduling can yield higher starch production compared to non-predictive approaches.
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Notes
- 1.
Because the simulation is finite, on the last several days (from the day \(T-N_{\text {p}}+2\) to day T), the prediction horizon based on current date exceeds the length of the simulation, resulting in errors. To solve this, the controller reduces the prediction horizon if it exceeds the length of the simulation.
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Acknowledgments
The authors thank Dr. Jaap Ottjes for his valuable comments and discussions. By the China Scholarship Council under grant 201406950004 this research is supported.
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Lin, X., Negenborn, R.R., Lodewijks, G. (2017). Quality-Aware Predictive Scheduling of Raw Perishable Material Transports. In: Freitag, M., Kotzab, H., Pannek, J. (eds) Dynamics in Logistics. Lecture Notes in Logistics. Springer, Cham. https://doi.org/10.1007/978-3-319-45117-6_6
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DOI: https://doi.org/10.1007/978-3-319-45117-6_6
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