Supported by the grant of National Natural Science Foundation of China(No.10771133);Key Disciplines of Shanghai Municipality(Operations Research and Control Theory S 30104)
supported by Hong Kong RGC Earmarked Grant (Grant No.CUHK418406);National Natural Science Foundation of China (Grant No.10771133)
In this paper,we consider the following indefinite complex quadratic maximization problem: maximize zHQz,subject to zk ∈ C and zkm = 1,k = 1,...,n,where Q is a Hermitian matrix with trQ = 0,z ∈ Cn is the decision ve...
Project supported by the National Natural Science Foundation of China (Grant No.10771133);the Research Fundation for the Doctoral Program of Higher Education (Grant No.200802800010);the Key Disciplines of Shanghai Municipality (GrantNo.s30104)
A reduction of truss topology design problem formulated by semidefinite optimization (SDO) is considered. The finite groups and their representations are introduced to reduce the stiffness and mass matrices of truss...
supported by the National Natural Science Foundation of China (Grant No.10771133)
Suboptimal alignments always reveal additional interesting biological features and have been successfully used to informally estimate the significance of an optimal alignment. Besides, traditional dynamic programming ...
supported by the National Natural Science Foundation of China (No. 10771133);the KeyDisciplines of Shanghai Municipality (Operations Research and Cybernetics) (No. S30104)
In this paper, we use the discontinuous exact penalty functions to solve the constrained minimization problems with an integral approach. We examine a general form of the constrained deviation integral and its analyti...
supported by the National Natural Science Foundation of China (Grant No.10771133);the Shanghai Leading Academic Discipline Project (Grant No.S30101);the Research Foundation for the Doctoral Program of Higher Education (Grant No.200802800010)
The choice of self-concordant functions is the key to efficient algorithms for linear and quadratic convex optimizations, which provide a method with polynomial-time iterations to solve linear and quadratic convex opt...
supported by the National Natural Science Foundation of China (Grant No.10771133);the Shanghai Leading Academic Discipline Project (Grant Nos.J50101, S30104)
A penalized interior point approach for constrained nonlinear programming is examined in this work. To overcome the difficulty of initialization for the interior point method, a problem equivalent to the primal proble...