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Minimum-cost flow problem. The minimum-cost flow problem ( MCFP) is an optimization and decision problem to find the cheapest possible way of sending a certain amount of flow through a flow network. A typical application of this problem involves finding the best delivery route from a factory to a warehouse where the road network has some ...
Network flow problem. In combinatorial optimization, network flow problems are a class of computational problems in which the input is a flow network (a graph with numerical capacities on its edges), and the goal is to construct a flow, numerical values on each edge that respect the capacity constraints and that have incoming flow equal to ...
To solve this problem one uses a variation of the circulation problem called bounded circulation which is the generalization of network flow problems, with the added constraint of a lower bound on edge flows. Let G = (V, E) be a network with s,t ∈ V as the source and the sink nodes.
IPv4 address exhaustion is the depletion of the pool of unallocated IPv4 addresses. Because the original Internet architecture had fewer than 4.3 billion addresses available, depletion has been anticipated since the late 1980s when the Internet started experiencing dramatic growth. This depletion is one of the reasons for the development and ...
Pipe network analysis. In fluid dynamics, pipe network analysis is the analysis of the fluid flow through a hydraulics network, containing several or many interconnected branches. The aim is to determine the flow rates and pressure drops in the individual sections of the network. This is a common problem in hydraulic design.
In computing, the Two Generals' Problem is a thought experiment meant to illustrate the pitfalls and design challenges of attempting to coordinate an action by communicating over an unreliable link. In the experiment, two generals are only able to communicate with one another by sending a messenger through enemy territory.
Behnke relied only on the sign of the gradient when training his Neural Abstraction Pyramid [22] to solve problems like image reconstruction and face localization. [ citation needed ] Neural networks can also be optimized by using a universal search algorithm on the space of neural network's weights, e.g., random guess or more systematically ...
Increasing the transmission power of the nodes can solve the hidden node problem by allowing the cell around each node to increase in size, encompassing all of the other nodes. This configuration enables the non-hidden nodes to detect, or hear, the hidden node. If the non-hidden nodes can hear the hidden node, the hidden node is no longer hidden.
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