The use of integer programming to select bulls across breeding companies with volume price discounts.
Optimization programs are currently used to aid in the selection of bulls to be used in herd breeding programs. While these programs offer a systematic approach to the problem of semen selection, they ignore the impact of volume discounts. Volume discounts are discounts that vary depending on the number of straws purchased. The dynamic nature of volume discounts means that, in order to be adequately accounted for, they must be considered in the optimization routine. Failing to do this creates a missed economic opportunity because the potential benefits of optimally selecting and combining breeding company discount opportunities are not captured. To address these issues, an integer program was created which used binary decision variables to incorporate the effects of quantity discounts into the optimization program. A consistent set of trait criteria was used to select a group of bulls from 3 sample breeding companies. Three different selection programs were used to select the bulls, 2 traditional methods and the integer method. After the discounts were applied using each method, the integer program resulted in the lowest cost portfolio of bulls. A sensitivity analysis showed that the integer program also resulted in a low cost portfolio when the genetic trait goals were changed to be more or less stringent. In the sample application, a net benefit of the new approach over the traditional approaches was a 12.3 to 20.0% savings in semen cost.
McConnel
M B
MB
University of Pennsylvania, School of Veterinary Medicine Center for Animal Health and Productivity 382 West Street Road, Kennett Square, PA 19348, USA. mmcconne@wharton.upenn.edu
Galligan
D T
DT
D000818:Animals; D001947:Breeding / Q000191:economics* / Q000379:methods; D002417:Cattle / Q000235:genetics; D003362:Cost-Benefit Analysis; D003661:Decision Support Techniques; D016014:Linear Models; D008297:Male; D019655:Quantitative Trait, Heritable; D012641:Selection, Genetic; D012984:Software