In this paper,a new model for inverse network flow problems,robust partial inverse problem is presented. For a given partial solution,the robust partial inverse problem is to modify the coefficients optimally such tha...In this paper,a new model for inverse network flow problems,robust partial inverse problem is presented. For a given partial solution,the robust partial inverse problem is to modify the coefficients optimally such that all full solutions containing the partial solution become optimal under new coefficients. It has been shown that the robust partial inverse spanning tree problem can be formulated as a combinatorial linear program,while the robust partial inverse minimum cut problem and the robust partial inverse assignment problem can be solved by combinatorial strongly polynomial algorithms.展开更多
The idea of the inverse optimization problem is to adjust the values of the parameters so that the observed feasible solutions are indeed optimal.The modification cost is measured by different norms,such asl1,l2,l∞no...The idea of the inverse optimization problem is to adjust the values of the parameters so that the observed feasible solutions are indeed optimal.The modification cost is measured by different norms,such asl1,l2,l∞norms and the Hamming distance,and the goal is to adjust the parameters as little as possible.In this paper,we consider the inverse maximum flow problem under the combination of the weighted l2 norm and the weighted Hamming distance,i.e.,the modification cost is fixed in a given interval and depends on the modification out of the given interval.We present a combinatorial algorithm which can be finished in O(nm)to solve it due to the minimum cut of the residual network.展开更多
基金Supported by National Natural Science Foundation of China(79790 1 30 ) and National863Hi- TechProject(863- 30 6- ZT0 4 - 0 4 -
文摘In this paper,a new model for inverse network flow problems,robust partial inverse problem is presented. For a given partial solution,the robust partial inverse problem is to modify the coefficients optimally such that all full solutions containing the partial solution become optimal under new coefficients. It has been shown that the robust partial inverse spanning tree problem can be formulated as a combinatorial linear program,while the robust partial inverse minimum cut problem and the robust partial inverse assignment problem can be solved by combinatorial strongly polynomial algorithms.
基金This research is supported by the Fundamental Research Funds for the Central Universities(No.20720190068)the China Scholarship Council(No.201706315073).
文摘The idea of the inverse optimization problem is to adjust the values of the parameters so that the observed feasible solutions are indeed optimal.The modification cost is measured by different norms,such asl1,l2,l∞norms and the Hamming distance,and the goal is to adjust the parameters as little as possible.In this paper,we consider the inverse maximum flow problem under the combination of the weighted l2 norm and the weighted Hamming distance,i.e.,the modification cost is fixed in a given interval and depends on the modification out of the given interval.We present a combinatorial algorithm which can be finished in O(nm)to solve it due to the minimum cut of the residual network.
