
%0 Journal Article
%A Horton, B 
%T A method of using a genetic algorithm to examine the optimum structure of the Australian sheep breeding industry: open-nucleus breeding systems, MOET and AI
%J Australian Journal of Experimental Agriculture
%D 1996/05/01
%V 36
%N 3
%P 249-258
%K 
%R https://doi.org/10.1071/EA9960249
%U https://www.publish.csiro.au/paper/EA9960249 
%X A genetic algorithm was evaluated as a means of using a computer model to determine the optimum structure of the Australian sheep breeding industry. The model simulates an open-nucleus 3-tiered sheep breeding system to investigate the benefit of strategies such as multiple ovulation and embryo transfer (MOET) and artificial insemination (AI) in terms of both genetic improvement and dollar values. The model indicated that both MOET and non- MOET systems benefit from an open nucleus, and both could also benefit from the promotion of some ewes from the commercial flocks. However, MOET systems require a relatively large number of rams, whereas non- MOET systems should have a smaller number of rams despite the much larger number of ewes needed. Under the conditions studied here, there was only limited advantage of MOET over non-MOET schemes. The optimum structure of the MOET, non-MOET and closed systems differ substantially. A genetic algorithm is a simple method for considering a single change (such as reproductive rate, or open v. closed) that may require major changes in the industry structure to achieve the full benefits. The method could also be of value in many other situations requiring optimisation of complex models. 
