Graphs model the connections in a network and are widely applicable to a variety of physical, biological, and information systems. You can use graphs to model the neurons in a brain, the flight patterns of an airline, and much more.

Apr 1, 2024 · Graph algorithms are methods used to manipulate and analyze graphs, solving various range of problems like finding the shortest path, cycles detection. If you are looking for difficulty-wise list of problems, please refer to Graph Data Structure.

Graph Traversal The most basic graph algorithm that visits nodes of a graph in certain order Used as a subroutine in many other algorithms We will cover two algorithms – Depth-First Search (DFS): uses recursion (stack) – Breadth-First Search …

In communication networks, graph algorithms optimize data routing, enhance network security, and manage traffic flow. Biological networks utilize graph models to decipher protein interactions, gene regulatory mechanisms, and neural connectivity, contributing to advances in …

In this lecture, we will ask a question of a different sort. We start with a directed weighted graph G with two distinguished vertices s (the source) and. t (the sink). We interpret the edges as unidirectional water pipes, with an edge’s capacity indicated by its weight.

Jul 12, 2023 · In network analysis, the study and comprehension of complex systems in numerous fields, such as social networks, transportation networks, and biological networks, are made possible by the crucial...

Dec 3, 2023 · Network analysis examines the relationships between interconnected entities, represented as nodes and edges in a network. This versatile tool has applications in various domains, including...

Nov 6, 2023 · Social Networks: Graphs represent connections between users on social media platforms, helping in friend recommendations and network analysis. Transportation Networks: Road networks, flight...

Aug 22, 2022 · Network : A network is a circuit which is a sequence of adjacent nodes that comes back to the starting node. A circuit containing all the nodes of a graph is known as Hamiltonian Circuit.

Graph-based network flow algorithms excel in speed and efficiency due to their optimised algorithm complexity. They exploit the network topology to quickly find the highest capacity paths, making them ideal for data-heavy workloads.