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Optimisation of contribution of candidate parents to maximise genetic gain and restricting inbreeding using semidefinite programming (Open Access publication)

机译:使用半定程序优化候选父母的贡献,以最大化遗传增益并限制近交(开放获取出版物)

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摘要

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.
机译:提出了一种使用半定规划(SDP)优化候选人的遗传贡献以控制后代近交的方法。进行配制以最大化遗传增益,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小化近亲繁殖。还显示了对固定缴费候选人的适应说明。使用小的但可追溯的数值示例,将SDP方法与基于拉格朗日乘数(RSRO)的替代方法进行了比较。与RSRO不同,SDP方法始终找到了在近交限制上最大化遗传增益的最佳解决方案,而RSRO在某些情况下未能做到这一点。在这些情况下,使用RSRO获得的解决方案的预期收益要比使用SDP发现的最佳解决方案(分配的贡献差异很大)的预期收益低1.5–9%。总之,SDP是解决缴费问题的可靠且灵活的方法。

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