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Australian Sugar Mills Optimise Siding Rosters to Increase Profitability

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  • Andrew Higgins
  • Steve Postma

Abstract

Increasing cost/price ratios in sugarcane production and the pressure to remain internationally competitive have forced Australian sugar mills to reduce capital and operational costs. Increased utilisation of transport infrastructure through improved rostering of harvesting groups into sugarcane rail and road sidings provides an opportunity to reduce transport and harvesting costs. Generating and maintaining siding rosters manually also requires high labour costs because of the time-consuming effort to simultaneously balance limited capacities in the transportation facilities with costs of harvester movements as well as the social considerations of equity between growers. To address this complex socio-economic issue, participatory research was undertaken with a large sugar milling company in Australia to implement siding rosters that were optimised using a tabu search. This resulted in an original adoption of staff rosters produced using operations research techniques, which substantially reduced the up-front and on-going labour costs of planning and maintaining an effective roster throughout the 2002 harvest season. Copyright Kluwer Academic Publishers 2004

Suggested Citation

  • Andrew Higgins & Steve Postma, 2004. "Australian Sugar Mills Optimise Siding Rosters to Increase Profitability," Annals of Operations Research, Springer, vol. 128(1), pages 235-249, April.
    • Handle: RePEc:spr:annopr:v:128:y:2004:i:1:p:235-249:10.1023/b:anor.0000019107.68291.36
    DOI: 10.1023/B:ANOR.0000019107.68291.36
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    Citations

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    Cited by:

    1. Rafael Paiva & Reinaldo Morabito, 2009. "An optimization model for the aggregate production planning of a Brazilian sugar and ethanol milling company," Annals of Operations Research, Springer, vol. 169(1), pages 117-130, July.
    2. Kamal Lamsal & Philip C. Jones & Barrett W. Thomas, 2017. "Sugarcane Harvest Logistics in Brazil," Transportation Science, INFORMS, vol. 51(2), pages 771-789, May.
    3. Karsu, Özlem & Morton, Alec, 2015. "Inequity averse optimization in operational research," European Journal of Operational Research, Elsevier, vol. 245(2), pages 343-359.
    4. Grunow, M. & Gunther, H.-O. & Westinner, R., 2007. "Supply optimization for the production of raw sugar," International Journal of Production Economics, Elsevier, vol. 110(1-2), pages 224-239, October.
    5. Yang Bai & He Yang & Yu Zhao & Min Zhang & Jinyuan Qin & Feng Mi, 2020. "Optimizing the Raw Material Supply Chain of the Wood Biomass Power Generation Industry for Different Stakeholders’ Benefits: An Analysis of Inner Mongolia, China," Sustainability, MDPI, vol. 12(5), pages 1-15, March.
    6. Helenice de Oliveira Florentino & Chandra Irawan & Angelo Filho Aliano & Dylan F. Jones & Daniela Renata Cantane & Jonis Jecks Nervis, 2018. "A multiple objective methodology for sugarcane harvest management with varying maturation periods," Annals of Operations Research, Springer, vol. 267(1), pages 153-177, August.

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