For ill-posed bilevel programming problem,the optimistic solution is always the best decision for the upper level but it is not always the best choice for both levels if the authors consider the model's satisfacto...For ill-posed bilevel programming problem,the optimistic solution is always the best decision for the upper level but it is not always the best choice for both levels if the authors consider the model's satisfactory degree in application.To acquire a more satisfying solution than the optimistic one to realize the two levels' most profits,this paper considers both levels' satisfactory degree and constructs a minimization problem of the two objective functions by weighted summation.Then,using the duality gap of the lower level as the penalty function,the authors transfer these two levels problem to a single one and propose a corresponding algorithm.Finally,the authors give an example to show a more satisfying solution than the optimistic solution can be achieved by this algorithm.展开更多
In this paper we study nonlinear Lagrangian methods for optimization problems with side constraints. Nonlinear Lagrangian dual problems are introduced and their relations with the original problem are established. Mor...In this paper we study nonlinear Lagrangian methods for optimization problems with side constraints. Nonlinear Lagrangian dual problems are introduced and their relations with the original problem are established. Moreover, a least root approach is investigated for these optimization problems.展开更多
基金supported by the National Science Foundation of China under Grant No.71171150the National Natural Science Foundation of ChinaTian Yuan Foundation under Grant No.11226226
文摘For ill-posed bilevel programming problem,the optimistic solution is always the best decision for the upper level but it is not always the best choice for both levels if the authors consider the model's satisfactory degree in application.To acquire a more satisfying solution than the optimistic one to realize the two levels' most profits,this paper considers both levels' satisfactory degree and constructs a minimization problem of the two objective functions by weighted summation.Then,using the duality gap of the lower level as the penalty function,the authors transfer these two levels problem to a single one and propose a corresponding algorithm.Finally,the authors give an example to show a more satisfying solution than the optimistic solution can be achieved by this algorithm.
文摘In this paper we study nonlinear Lagrangian methods for optimization problems with side constraints. Nonlinear Lagrangian dual problems are introduced and their relations with the original problem are established. Moreover, a least root approach is investigated for these optimization problems.
