Quality-Aware Predictive Scheduling of Raw Perishable Material Transports

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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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Lin, X., Negenborn, R. R., & Lodewijks, G. (2017). Quality-Aware Predictive Scheduling of Raw Perishable Material Transports. In Lecture Notes in Logistics (pp. 65–76). Springer Science and Business Media B.V. https://doi.org/10.1007/978-3-319-45117-6_6

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