Mayer, D.G. and Belward, J.A. and Burrage, K. (1999) Performance of Genetic Algorithms and Simulated Annealing in the Economic Optimization of a Herd Dynamics Model. Environment International, 25 (6-7). pp. 899-905.
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Article Link(s): http://dx.doi.org/10.1016/S0160-4120(99)00044-6
Publisher URL: http://www.elsevier.com
This study focuses on replicated exploratory optimizations of a large and difficult beef herd dynamics model, using the net present value over a 10-year planning horizon as the variable of interest. Faced with a practical search-space of the order of 10100 possible management decision combinations, the thorough but slow search pattern of simulated annealing struggled, on average falling 1.2% short of the global optimum of the system. By comparison, the cross-breeding and mutating nature of the genetic algorithm searches usually produced good results, averaging 0.1% from the global optimum. Also, these were achieved with about half the computing time used by the simulated annealing optimizations. Hence, for this problem, genetic algorithms proved the superior method.
|Additional Information:||© Elsevier Ltd.|
|Keywords:||Agricultural systems; herd dynamics; cross-breeding.|
|Subjects:||Science > Statistics > Simulation modelling|
|Deposited On:||09 Dec 2003|
|Last Modified:||16 Mar 2009 04:06|
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