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Scheduling of brand production and shipping within a sugar supply chain

Author

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  • A Higgins

    (CSIRO Sustainable Ecosystems)

  • G Beashel

    (Queensland Sugar Limited)

  • A Harrison

    (Queensland Sugar Limited)

Abstract

The Australian sugar industry exports about 90% of its five million tonne annual sugar production on the open market to customers in several countries, who request various brands of raw sugar. In planning at this interface of the sugar supply chain, an objective is to schedule the brands of sugar each mill produces throughout the annual harvest season, along with the ports that each ship loads at, to minimize total costs of sugar production and shipping. The complexity of such planning for the sugar industry has been overcome through the development and solution of a mixed-integer programming model to perform the task. The model is used as an annual planning tool to obtain a base schedule, as well as a rescheduling tool to revise the plan during the year as mill production rates and shipments change. Using the Australian sugar industry as a case study, this paper focuses on the mathematical model and solution using two known meta-heuristics based on local search. Using the 2002/2003 and 2003/2004 financial years, a comparison is made between the schedules produced in practice using manual methods and those using the model, which show a total potential cost savings of up to AU$4.0 M for the 2 years.

Suggested Citation

  • A Higgins & G Beashel & A Harrison, 2006. "Scheduling of brand production and shipping within a sugar supply chain," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(5), pages 490-498, May.
    • Handle: RePEc:pal:jorsoc:v:57:y:2006:i:5:d:10.1057_palgrave.jors.2602025
    DOI: 10.1057/palgrave.jors.2602025
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    References listed on IDEAS

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    1. Higgins, Andrew & Antony, George & Sandell, Gary & Davies, Ian & Prestwidge, Di & Andrew, Bill, 2004. "A framework for integrating a complex harvesting and transport system for sugar production," Agricultural Systems, Elsevier, vol. 82(2), pages 99-115, November.
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    4. K T Park & K H Kim, 2002. "Berth scheduling for container terminals by using a sub-gradient optimization technique," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(9), pages 1054-1062, September.
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    Citations

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    Cited by:

    1. Higgins, Andrew & Thorburn, Peter & Archer, Ainsley & Jakku, Emma, 2007. "Opportunities for value chain research in sugar industries," Agricultural Systems, Elsevier, vol. 94(3), pages 611-621, June.
    2. Bilgen, Bilge & Ozkarahan, Irem, 2007. "A mixed-integer linear programming model for bulk grain blending and shipping," International Journal of Production Economics, Elsevier, vol. 107(2), pages 555-571, June.
    3. Soysal, Mehmet & Bloemhof-Ruwaard, Jacqueline.M. & Meuwissen, Miranda P.M. & van der Vorst, Jack G.A.J., 2012. "A Review on Quantitative Models for Sustainable Food Logistics Management," International Journal on Food System Dynamics, International Center for Management, Communication, and Research, vol. 3(2), pages 1-20, December.
    4. 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.
    5. Kopanos, Georgios M. & Puigjaner, Luis & Georgiadis, Michael C., 2012. "Simultaneous production and logistics operations planning in semicontinuous food industries," Omega, Elsevier, vol. 40(5), pages 634-650.
    6. Pierre Hansen & Nenad Mladenović & José Moreno Pérez, 2010. "Variable neighbourhood search: methods and applications," Annals of Operations Research, Springer, vol. 175(1), pages 367-407, March.
    7. Soysal, Mehmet & Bloemhof, Jacqueline M. & van der Vorst, Jack G.A.J., 2012. "A Review of Quantitative Models for Sustainable Food Logistics Management: Challenges and Issues," 2012 International European Forum, February 13-17, 2012, Innsbruck-Igls, Austria 144974, International European Forum on System Dynamics and Innovation in Food Networks.
    8. Kusumastuti, Ratih Dyah & Donk, Dirk Pieter van & Teunter, Ruud, 2016. "Crop-related harvesting and processing planning: a review," International Journal of Production Economics, Elsevier, vol. 174(C), pages 76-92.
    9. Stüve, David & van der Meer, Robert & Lütke Entrup, Matthias & Agha, Mouhamad Shaker Ali, 2020. "Supply chain planning in the food industry," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Kersten, Wolfgang & Blecker, Thorsten & Ringle, Christian M. (ed.), Data Science and Innovation in Supply Chain Management: How Data Transforms the Value Chain. Proceedings of the Hamburg International Conference of Lo, volume 29, pages 317-353, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.

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