The energy variational formula based on the principle of minimum potential energy is proposed for the plates constrained at arbitrary points. As an instance, the orthotropic large deflection rectangular thin plates wi...The energy variational formula based on the principle of minimum potential energy is proposed for the plates constrained at arbitrary points. As an instance, the orthotropic large deflection rectangular thin plates with four free edges and transverse displacement constraints under uniform transverse load are discussed. The generalized Fourier series are used as the trial functions of the transverse displacement and the stress function to establish the essential equations, which are linearized by means of the incremental method of load and displacement constraint. In the end of the paper, several computational results are compared with the former literature. Moreover, one typical example is demonstrated through advanced experimental technique. The result shows the accuracy is satisfied well.展开更多
In this paper, we give a new generalized gradient projection algorithm for nonlinear optimization problems with arbitrary initial point. This new algorithm has some important advantages as follows: (1) The algorithm d...In this paper, we give a new generalized gradient projection algorithm for nonlinear optimization problems with arbitrary initial point. This new algorithm has some important advantages as follows: (1) The algorithm does not require initial feasible point; (2) It can deal with nonlinear equality and inequality constraints problems; (3) The structure of our algorithm is very simple;(4) Under some mild assumptions, it has global convergence.展开更多
This paper presents a new algorithm for optimization problems with nonlinear inequality constricts. At each iteration, the algorithm generates the search direction by solving only one quadratic programming (QP), and ...This paper presents a new algorithm for optimization problems with nonlinear inequality constricts. At each iteration, the algorithm generates the search direction by solving only one quadratic programming (QP), and then making a simple correction for the solution of the QP, moreover this new algorithm needn’t to do searching. The other advantage is that it may not only choose any point in En as a starting point, but also escape from the complex penalty function and diameter. moreover the iteration point will be a feasible descent sequence whenever some iteration point gets into the feasible region. So we call it subfeasible method.Under mild assumptions,the new algorithm is shown to possess global and two step superlinear convergence.展开更多
文摘The energy variational formula based on the principle of minimum potential energy is proposed for the plates constrained at arbitrary points. As an instance, the orthotropic large deflection rectangular thin plates with four free edges and transverse displacement constraints under uniform transverse load are discussed. The generalized Fourier series are used as the trial functions of the transverse displacement and the stress function to establish the essential equations, which are linearized by means of the incremental method of load and displacement constraint. In the end of the paper, several computational results are compared with the former literature. Moreover, one typical example is demonstrated through advanced experimental technique. The result shows the accuracy is satisfied well.
文摘In this paper, we give a new generalized gradient projection algorithm for nonlinear optimization problems with arbitrary initial point. This new algorithm has some important advantages as follows: (1) The algorithm does not require initial feasible point; (2) It can deal with nonlinear equality and inequality constraints problems; (3) The structure of our algorithm is very simple;(4) Under some mild assumptions, it has global convergence.
文摘This paper presents a new algorithm for optimization problems with nonlinear inequality constricts. At each iteration, the algorithm generates the search direction by solving only one quadratic programming (QP), and then making a simple correction for the solution of the QP, moreover this new algorithm needn’t to do searching. The other advantage is that it may not only choose any point in En as a starting point, but also escape from the complex penalty function and diameter. moreover the iteration point will be a feasible descent sequence whenever some iteration point gets into the feasible region. So we call it subfeasible method.Under mild assumptions,the new algorithm is shown to possess global and two step superlinear convergence.
