An operations research approach to the problem of the sugarcane selection

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.