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.
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Calija, V., Higgins, A.J., Jackson, P.A. et al. An Operations Research Approach to the Problem of the Sugarcane Selection. Annals of Operations Research 108, 123–142 (2001). https://doi.org/10.1023/A:1016054911470
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DOI: https://doi.org/10.1023/A:1016054911470