In this paper, uncertain dynamic network flow problems (UDNFPs) are formulated, and an algorithm is proposed to solve them by noting that arc capacities are uncertain (may vary with time or not), and flow varies over time in each arc. Here, uncertainty refers to nondeterministic states, in which some factors are uncertain and cannot be determined by the probability theory. Since the uncertainty...

We consider semi-continuous network flow problems, that is, a class of network flow problems where some of the variables are restricted to be semi-continuous. We introduce the semi-continuous inflow set with variable upper bounds as a relaxation of general semi-continuous network flow problems. Two particular cases of this set are considered, for which we present complete descriptions of the co...

A flow cache is a fundamental building block for flowbased traffic processing. Its efficiency is critical for the overall performance of a number of networked devices and systems. The efficiency is mainly dependent on a utilized replacement policy. This work proposes an approach based on Genetic Algorithm. The proposed approach starts from recorded traffic traces and uses Genetic Algorithm to e...

The Minimum Cost Network Flow Problem (MCNFP) includes a wide range of combinatorial optimization problems. Many applications exist for MCNFPs for instance supply chains, logistics, production planning, communications and transportations. Concave costs are, in many applications, more realistic than linear ones because of the association of prices with economies of scale. When concave costs are ...

The well-studied Interferometric Synthetic Aperture Radar (InSAR) problem for digital elevation map generation involves the derivation of topography from radar phase. The topography is a function of the full phase, whereas the measured phase is known modulo , necessitating the process of recovering full phase values via phase unwrapping. This mathematical process becomes difficult through the p...

• A type of shallow modules are proposed to directly predict the feature flow for alignment in a single network. Self-supervision learning is introduced further improve quality predicted flow. new state-of-the-art performance shown by comparing with other methods, while fast inference speed maintained. Optical flow, which expresses pixel displacement, widely used many computer vision tasks prov...

Underbalanced drilling as multiphase flow is done in oil drilling operation in low pressure reservoir or highly depleted mature reservoir. Correct determination of the pressure loss of three phase fluids in drilling annulus is essential in determination of hydraulic horsepower requirements during drilling operations. In this paper the pressure loss of solid-gas-liquid three-phase fluids flow in...