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A bi-objective chance constrained programming model for efficient crop harvest scheduling

Abstract : One of the main purposes of the agricultural supply chains management is to organize efficiently the processes of harvesting, transport and storage of the cereal production from the growing fields to the storage facilities. The current configuration of the supply chain, where farmers can improve a continuous process of harvesting, can be enhanced by organizing a buffer crop storage (work-in-process) directly in the growing fields. Crop harvesting must be completed as soon as possible, because delayed harvest increases both the risk of yield and quality losses. Motivated by a real life study case encountered at a typical French agricultural cooperative, this paper presents a bi-objective chance constrained programming model where the optimization criteria deal with crop quality degradation and inventory control, under climate uncertainty. Due to computational complexity and time limitations, scalarization techniques combined with (1 − \alpha)-pertinent scenarios are used. Numerical results reported that the bi-response chance constrained approach offers a spectrum of non-dominated solutions satisfying a desired confidence level.
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Submitted on : Thursday, May 28, 2020 - 11:36:49 PM
Last modification on : Sunday, June 26, 2022 - 1:40:52 AM


  • HAL Id : hal-02644854, version 1



Valeria Borodin, Jean Bourtembourg, Faicel Hnaien, Nacima Labadie. A bi-objective chance constrained programming model for efficient crop harvest scheduling. 18th International Symposium on Inventories, Aug 2014, Budapest, Hungary. ⟨hal-02644854⟩



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