Robust Optimization for Selection of Genotypes with Maximum Genetic Gain

論文翻譯標題: 使用Robust 優化技巧以選擇具有最大獲益的基因型態
  • 蔡 幸樺

學生論文: Master's Thesis


In this thesis we first review the three conic relaxation: SDP (Semi-definite programming) LP (Linear programming) and SOCP (Second-order cone programming) proposed in S Safarina et al (2017) for the optimum selection of genotypes that maximize genetic gain Then we consider the robust optimization to the LP relaxation and incorporate with a steepest ascent method to acquire an appropriate solution for the equal deployment(ED) problem subject to uncertainty data At last we conduct numerical experiments to test the feasibility incurred by the perturbation
監督員Ruey-Lin Sheu (Supervisor)