Jagannath Aryal and Don Kulasiri and Dishi Liu
Optimization Approaches for a Complex Dairy Farm Simulation Model
405 - 411
2008
2
2
International Journal of Computer and Information Engineering
https://publications.waset.org/pdf/935
https://publications.waset.org/vol/14
World Academy of Science, Engineering and Technology
This paper describes the optimization of a complex
dairy farm simulation model using two quite different methods of
optimization, the Genetic algorithm (GA) and the Lipschitz
BranchandBound (LBB) algorithm. These techniques have been
used to improve an agricultural system model developed by Dexcel
Limited, New Zealand, which describes a detailed representation of
pastoral dairying scenarios and contains an 8dimensional parameter
space. The model incorporates the submodels of pasture growth and
animal metabolism, which are themselves complex in many cases.
Each evaluation of the objective function, a composite &039;Farm
Performance Index (FPI)&039;, requires simulation of at least a oneyear
period of farm operation with a daily timestep, and is therefore
computationally expensive. The problem of visualization of the
objective function (response surface) in highdimensional spaces is
also considered in the context of the farm optimization problem.
Adaptations of the sammon mapping and parallel coordinates
visualization are described which help visualize some important
properties of the models output topography. From this study, it is
found that GA requires fewer function evaluations in optimization
than the LBB algorithm.
Open Science Index 14, 2008