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An Operations Research Approach to the Problem of the Sugarcane Selection
Authors:Vanja Calija  Andrew J. Higgins  Phillip A. Jackson  Leone M. Bielig  Danny Coomans
Affiliation:(1) CRC for Sustainable Sugar Production, James Cook University, PO Box 6811, Smithfield, QLD 4878, Australia;(2) CSIRO Sustainable Ecosystems, 120 Meiers Road, Indooroopilly QLD 4068, Australia;(3) Davies Laboratory, CSIRO Plant Industry, Private Mail Bag, Aitkenvale, QLD 4814, Australia;(4) Department of Tropical Plant Science, James Cook University, Aitkenvale, QLD 4814, Australia;(5) Australia
Abstract:Selection for superior clones is the most important aspect of sugar cane improvement programs, and is a long and expensive process. While studies have investigated different components of selection independently, there has not been a whole system approach to improve the process. This study observes the problem as an integrated system, where if one parameter changes the state of the whole system changes. A computer based stochastic simulation model that accurately represents the selection was developed. This paper describes the simulation model, showing its accuracy as well as how a combination of dynamic programming and branch and bound can be applied to the model to optimise the selection system, giving a new application of these techniques. The model can be directly applied to any region targeted by sugarcane breeding programs or to other clonally propagated crops.
Keywords:optimisation  simulation  stochastic models  agriculture
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