Name
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. |
Year | DOI | Venue |
|---|---|---|
2001 | 10.1023/A:1016054911470 | Annals OR |
Keywords | Field | DocType |
optimisation,simulation,stochastic models,agriculture | Stochastic simulation,Dynamic programming,Branch and bound,Mathematical optimization,Operations research,Stochastic modelling,Sugar cane,Mathematics | Journal |
Volume | Issue | ISSN |
108 | 1-4 | 1572-9338 |
Citations | PageRank | References |
3 | 0.42 | 1 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Vanja Calija | 1 | 3 | 0.42 |
| Andrew J. Higgins | 2 | 129 | 17.59 |
| Phillip A. Jackson | 3 | 3 | 0.42 |
| Leone M. Bielig | 4 | 3 | 0.42 |
| Danny Coomans | 5 | 105 | 19.07 |