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

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

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Article ID: iaor20023611
Country: Netherlands
Volume: 69
Issue: 3
Start Page Number: 199
End Page Number: 213
Publication Date: Sep 2001
Journal: Agricultural Systems
Authors: , ,
Keywords: simulation: applications, markov processes
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.

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