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Performance of Genetic Algorithms and Simulated Annealing in the Economic Optimization of a Herd Dynamics Model

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

Abstract

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.

Item Type:Article
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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