Shortest Paths: Negative Weights & Applications

Related lectures (29)

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Introduces the basics of graphs and networks, covering definitions, paths, trees, flows, circulation, and spanning trees.

Covers the concept of weighted graphs and the Greedy algorithm for finding a minimal spanning tree.

Explores Breadth-First Search and Dijkstra's algorithm for finding shortest paths in graphs.

Discusses the Ford-Fulkerson method and strongly connected components in graph algorithms.

Explores coordination among agents in networked control systems through graph theory and real-world examples.

Focuses on fixed points in graph theory and their implications in algorithms and analysis.

Covers graph algorithms, modeling relationships between objects, and traversal techniques like BFS and DFS.

Covers the fundamentals of integer programming and network flows in directed graphs.

Covers the basics of graph algorithms, focusing on modeling and representation of graphs in memory.

Discusses Union-Find data structures and Minimum Spanning Trees, covering algorithms and their applications in network design and optimization.