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Optimization Approaches for a Complex Dairy Farm Simulation Model


Aryal, J and Kulasiri, D and Liu, D, Optimization Approaches for a Complex Dairy Farm Simulation Model, International Journal of Computer and Information Engineering, 2, (3) pp. 157-163. ISSN 1307-2331 (2008) [Refereed Article]


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Copyright 2008 World Academy of Science, Engineering and Technology. Licensed under Creative Commons (Attribution unknown).

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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 Branch-and-Bound (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 8-dimensional parameter space. The model incorporates the sub-models of pasture growth and animal metabolism, which are themselves complex in many cases. Each evaluation of the objective function, a composite 'Farm Performance Index (FPI)', requires simulation of at least a one-year period of farm operation with a daily time-step, and is therefore computationally expensive. The problem of visualization of the objective function (response surface) in high-dimensional 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 model�s output topography. From this study, it is found that GA requires fewer function evaluations in optimization than the LBB algorithm.

Item Details

Item Type:Refereed Article
Keywords:genetic algorithm, Linux cluster, Lipschitz Branch-and-Bound, optimization
Research Division:Human Society
Research Group:Human geography
Research Field:Economic geography
Objective Division:Environmental Management
Objective Group:Other environmental management
Objective Field:Other environmental management not elsewhere classified
UTAS Author:Aryal, J (Dr Jagannath Aryal)
ID Code:80435
Year Published:2008
Deposited By:Geography and Environmental Studies
Deposited On:2012-10-31
Last Modified:2013-03-18
Downloads:314 View Download Statistics

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