This paper addresses a geometric programming problem,where the objective function and constraints are interval-valued functions.The concept of acceptable feasible region is introduced,and a methodology is developed t...This paper addresses a geometric programming problem,where the objective function and constraints are interval-valued functions.The concept of acceptable feasible region is introduced,and a methodology is developed to transform this model to a general optimization problem,which is free from interval uncertainty.Relationship between the solution of the original problem and the transformed problem is established.The methodology is illustrated through numerical examples.Solutions by the proposed method and previous methods are analyzed.展开更多
We propose a two-phase-SQP(Sequential Quadratic Programming)algorithm for equality-constrained optimization problem.In this paper,an iteration process is developed,and at each iteration,two quadratic sub-problems are ...We propose a two-phase-SQP(Sequential Quadratic Programming)algorithm for equality-constrained optimization problem.In this paper,an iteration process is developed,and at each iteration,two quadratic sub-problems are solved.It is proved that,under some suitable assumptions and without computing further higher-order derivatives,this iteration process achieves higher-order local convergence property in comparison to Newton-SQP scheme.Theoretical advantage and a note on l1 merit function associated to the method are provided.展开更多
文摘This paper addresses a geometric programming problem,where the objective function and constraints are interval-valued functions.The concept of acceptable feasible region is introduced,and a methodology is developed to transform this model to a general optimization problem,which is free from interval uncertainty.Relationship between the solution of the original problem and the transformed problem is established.The methodology is illustrated through numerical examples.Solutions by the proposed method and previous methods are analyzed.
文摘We propose a two-phase-SQP(Sequential Quadratic Programming)algorithm for equality-constrained optimization problem.In this paper,an iteration process is developed,and at each iteration,two quadratic sub-problems are solved.It is proved that,under some suitable assumptions and without computing further higher-order derivatives,this iteration process achieves higher-order local convergence property in comparison to Newton-SQP scheme.Theoretical advantage and a note on l1 merit function associated to the method are provided.
