In the Network Flow Interdiction problem an adversary attacks a network in order to minimize the maximum s-t-flow. Very little is known about the approximatibility of this problem despite decades of interest in it. We present the first approximation hardness, showing that Network Flow Interdiction and several of its variants cannot be much easier to approximate than Densest k-Subgraph. In parti...

We study the maximum flow problem in an undirected planar network with both edge and vertex capacities (EVC-network). A previous study reduces the minimum cut problem in an undirected planar EVC-network to the minimum edge-cut problem in another planar network with edge capacity only (EC-network), thus the minimum-cut or the maximum flow value can be computed in O(n log n) time. Based on this r...

In this paper, we consider an integer convex optimization problem where the objective function is the sum of separable convex functions (that is, of the form Σ(i,j)∈Q ij ij F (w ) + Σi∈P i i B ( ) μ ), the constraints are similar to those arising in the dual of a minimum cost flow problem (that is, of the form μi μj ≤ wij, (i, j) ∈ Q), with lower and upper bounds on variables. Let n = |P|, m = ...

The optimal power flow problem is concerned with finding a proper operating point for a power network while attempting to minimize some cost function and satisfy several network constraints. In this report we analyze the optimal power flow problem subject to contingency constraints, which demands that there be enough power to meet demands in the network in the event of contingencies such as a f...

accurate prediction of river flow is one of the most important factors in surface water recourses management especially during floods and drought periods. in fact deriving a proper method for flow forecasting is an important challenge in water resources management and engineering. although, during recent decades, some black box models based on artificial neural networks (ann), have been develop...

Extensions of Network Flow: Network flow is an important problem because it is useful in a wide variety of applications. We will discuss two useful extensions to the network flow problem. We will show that these problems can be reduced to network flow, and thus a single algorithm can be used to solve both of them. Many computational problems that would seem to have little to do with flow of flu...

in this study, a three–layer artificial neural network (ann) model was developed to predict the pressure gradient in horizontal liquid–liquid separated flow. a total of 455 data points were collected from 13 data sources to develop the ann model. superficial velocities, viscosity ratio and density ratio of oil to water, and roughness and inner diameter of pipe were used as input parameters of t...

Extensions of Network Flow: Network flow is an important problem because it is useful in a wide variety of applications. We will discuss two useful extensions to the network flow problem. We will show that these problems can be reduced to network flow, and thus a single algorithm can be used to solve both of them. Many computational problems that would seem to have little to do with flow of flu...