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Application of crop growth simulation and mathematical modeling to supply chain management in the Thai sugar industry

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  • Piewthongngam, Kullapapruk
  • Pathumnakul, Supachai
  • Setthanan, Kanchana

Abstract

The poorly integrated cane supply planning between mills and cane growers in the Northeast of Thailand generates an excess of cane supplies that exceeds the mills' capacity during the peak of harvest season. Each grower individually determines his/her cultivation plan by selecting planting dates and cultivars based on one's own preference without taking into account the individual mill's capacity and other growers' plans. This situation causes most sugarcane grown in this area to reach its mature stage at the same period. In this study, we propose a framework of cultivation planning to cope with the problem. The focus of the cultivation plan is a long-term plan to determine the cultivation time, the cultivar selection and the corresponding prospective harvesting time window for each field such that overall sugar production is optimized. The crop growth model and a mathematical model are employed for yield simulation and optimization task. The crop growth model enables decision-makers to visualize cane production of each individual field at different dates with different cultivars and allow decision-makers to apply the mathematical programming to cultivation planning. The suggested framework has the potential to increase sugar production by 23% when compared to the traditional method.

Suggested Citation

  • Piewthongngam, Kullapapruk & Pathumnakul, Supachai & Setthanan, Kanchana, 2009. "Application of crop growth simulation and mathematical modeling to supply chain management in the Thai sugar industry," Agricultural Systems, Elsevier, vol. 102(1-3), pages 58-66, October.
    • Handle: RePEc:eee:agisys:v:102:y:2009:i:1-3:p:58-66
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    References listed on IDEAS

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    Cited by:

    1. Mahasuweerachai, Phumsith & Suksawat, Jakrapun, 2022. "Incentives for mechanized cane harvesting in Thailand: A choice experiment," Journal of Asian Economics, Elsevier, vol. 78(C).
    2. Tuğçe Taşkıner & Bilge Bilgen, 2021. "Optimization Models for Harvest and Production Planning in Agri-Food Supply Chain: A Systematic Review," Logistics, MDPI, vol. 5(3), pages 1-27, August.
    3. Bocca, Felipe Ferreira & Rodrigues, Luiz Henrique Antunes & Arraes, Nilson Antonio Modesto, 2015. "When do I want to know and why? Different demands on sugarcane yield predictions," Agricultural Systems, Elsevier, vol. 135(C), pages 48-56.
    4. Helenice de O. Florentino & Dylan F. Jones & Chandra Ade Irawan & Djamila Ouelhadj & Banafesh Khosravi & Daniela R. Cantane, 2022. "An optimization model for combined selecting, planting and harvesting sugarcane varieties," Annals of Operations Research, Springer, vol. 314(2), pages 451-469, July.
    5. Junqueira, Rogerio de Ávila Ribeiro & Morabito, Reinaldo, 2019. "Modeling and solving a sugarcane harvest front scheduling problem," International Journal of Production Economics, Elsevier, vol. 213(C), pages 150-160.

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