Bin-objective shape optimization of arch dam based on linear programming model is discussed to minimize both dam volume and maximal tensile stress.The importance of weight coefficient of the above two objectives is ch...Bin-objective shape optimization of arch dam based on linear programming model is discussed to minimize both dam volume and maximal tensile stress.The importance of weight coefficient of the above two objectives is chosen according to the value of importance ratio.The influence of weight coefficient to the optimization result is discussed in detail and the numerical example shows that both the model and method proposed is doable.展开更多
We establish in this paper optimal parametric Lagrangian dual models for box constrained quadratic program based on the generalized D.C.(difference between convex) optimization approach,which can be reformulated as se...We establish in this paper optimal parametric Lagrangian dual models for box constrained quadratic program based on the generalized D.C.(difference between convex) optimization approach,which can be reformulated as semidefinite programming problems.As an application,we propose new valid linear constraints for rank-one relaxation.展开更多
基金Sponsored by the National Natural Science Foundation of China(Grant.50139010).
文摘Bin-objective shape optimization of arch dam based on linear programming model is discussed to minimize both dam volume and maximal tensile stress.The importance of weight coefficient of the above two objectives is chosen according to the value of importance ratio.The influence of weight coefficient to the optimization result is discussed in detail and the numerical example shows that both the model and method proposed is doable.
基金supported by National Natural Science Foundation of China(Grant Nos. 11001006 and 91130019/A011702)the Fund of State Key Laboratory of Software Development Environment (Grant No. SKLSDE-2011ZX-15.)
文摘We establish in this paper optimal parametric Lagrangian dual models for box constrained quadratic program based on the generalized D.C.(difference between convex) optimization approach,which can be reformulated as semidefinite programming problems.As an application,we propose new valid linear constraints for rank-one relaxation.
