What pattern of mate allocation to use. The objective aims for high merit of progeny, low costs of reproductive technology and low levels of inbreeding both in the short term and in the long term. The latter is an approximation to the ideal handling of juveniles and overlapping generations. A stochastic algorithm was developed to give integer solutions for x. This has features of both differential evolution and genetic algorithms.
Integer solutions are important here, as selections and matings are discrete.
It is also possible to set a constraint on x'Ax, by setting x'G as the criterion to maximise, and allocating a low fitness value to candidate solutions which result in x'Ax being above the constraint. Using the stochastic algorithm, it is also possible to set maximum contributions from each candidate or juvenile. Brian Grundy has also developed Theo Meuwissen's 'real' method to set maximum contributions. There is a NAG subroutine which can also be used. Accommodating costs Costs associated with using novel reproductive techniques can be simply accommodated in the stochastic method.