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Robust parameter settings of evolutionary algorithms for the optimisation of agricultural systems models

Mayer, D.G. and Belward, J.A. and Burrage, K. (2001) Robust parameter settings of evolutionary algorithms for the optimisation of agricultural systems models. Agricultural Systems, 69 (3). pp. 199-213.

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Article Link(s): http://dx.doi.org/10.1016/S0308-521X(01)00025-7

Publisher URL: http://www.elsevier.com

Abstract

Numerical optimisation methods are being more commonly applied to agricultural systems models, to identify the most profitable management strategies. The available optimisation algorithms are reviewed and compared, with literature and our studies identifying evolutionary algorithms (including genetic algorithms) as superior in this regard to simulated annealing, tabu search, hill-climbing, and direct-search methods. Results of a complex beef property optimisation, using a real-value genetic algorithm, are presented. The relative contributions of the range of operational options and parameters of this method are discussed, and general recommendations listed to assist practitioners applying evolutionary algorithms to the solution of agricultural systems.

Item Type:Article
Corporate Creators:Animal Science
Additional Information:© Elsevier Science Ltd.
Keywords:Optimisation; model; genetic algorithm; evolutionary algorithm; parameters.
Subjects:Science > Statistics > Simulation modelling
Deposited On:09 Dec 2003
Last Modified:09 Jun 2011 02:52

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