Optimisation of contribution of candidate parents to maximise genetic gain and restricting inbreeding using semidefinite programming - (Open Access publication)
Optimisation of contribution of candidate parents to maximise genetic gain and restricting inbreeding using semidefinite programming - (Open Access publication)
复制标题
DOI：
10.1051/gse:2006031
复制
发表时间：
2007-01-01
影响因子：
4.1
通讯作者：
Woolliams, John A.
中科院分区：
文献类型：
--
作者：
Pong-Wong, Ricardo;Woolliams, John A.
提出了一种利用半定规划（SDP）优化候选个体遗传贡献以控制后代近交的方法。制定了最大限度地提高遗传增益，同时将近亲繁殖限制在预设值，并在不考虑增益的情况下最大限度地减少近亲繁殖。还显示了为考虑到有固定缴款的候选人而作出的调整。使用小但可追踪的数值例子，SDP方法进行了比较与基于拉格朗日乘子（RSRO）的替代方案。SDP方法总是找到最佳的解决方案，最大限度地提高遗传增益在任何水平的限制施加在近亲繁殖，不像RSRO未能做到这一点，在几种情况下。对于这些情况，从RSRO获得的解决方案的预期收益比从SDP找到的最佳解决方案的预期收益低1.5-9%，分配的贡献变化很大。因此，SDP是一个可靠的和灵活的方法来解决贡献问题。
An approach for optimising genetic contributions of candidates to control inbreeding in the offspring generation using semidefinite programming (SDP) was proposed. Formulations were done for maximising genetic gain while restricting inbreeding to a preset value and for minimising inbreeding without regard of gain. Adaptations to account for candidates with fixed contributions were also shown. Using small but traceable numerical examples, the SDP method was compared with an alternative based upon Lagrangian multipliers (RSRO). The SDP method always found the optimum solution that maximises genetic gain at any level of restriction imposed on inbreeding, unlike RSRO which failed to do so in several situations. For these situations, the expected gains from the solution obtained with RSRO were between 1.5-9% lower than those expected from the optimum solution found with SDP with assigned contributions varying widely. In conclusion SDP is a reliable and flexible method for solving contribution problems.