PPT-Dijkstra

W orked E xample d c g h a e f i b 4 4 8 5 8 11 30 14 7 9 6 7 Dijkstras algorithm Finds Shortest Path Tree from initial node a Path in tree from a to every node is the shortest path in the graph from a to that node . Dijkstra JK Competition Envy or Sn obbism How Popularity and Friendships Shape Antipathy Networks of Adolescents Journal of Research on Adolescence in press brPage 2br Popularity Antipathy and Friendship Networks 2 Acknowledgements This study was What do we mean by “weakest”?lIf A = B but not (B = A), then B is “weaker” than A, and A is “stronger” than B.lThe weakest possible predicate is the one that is identic Fig.2.Dijkstra'salgorithminanimperativeprogramminglanguage.WhiletheprograminFigure1issuccinct,itfailstoterminateinthepresenceofcyclesbecausethepathlengthsareunbounded.Evenifthedatacontainsnocycles,exi Navid. . adham. History. Dijkstra: 1959. Dantzig. . method: 1960 . “On the shortest route through a network” / management . science. Just an idea!. Berge and . Ghouila-Houri. : 1962. Incorrect stopping criterion. and Shavit-Francez termination algorithms. Index :. Introduction. Experimental Setup. Result Analysis. Conclusion. Future Work. Introduction. Dijkstra-Scholten. algorithm detects the termination of a centralized basic computation.. Shortest Path. Dijkstra’s. Algorithm - Picture. Dijkstra’s. Algorithm – Shortest Path. Dijkstra’s. Algorithm - Analysis. Shortest Path’s – on a DAG. All Points Shortest Path – Floyd’s . Minimum spanning . t. ree (MST). is a spanning tree whose weight is no larger than any other spanning tree. Prim . v.s. . . Kruskal. Prim:. At each time, add an edge connecting tree vertex and non-tree vertex. Minimum spanning . t. ree (MST). is a spanning tree whose weight is not larger than any other spanning tree. Prim . v.s. . . Kruskal. Prim:. At each time, add an edge connecting tree vertex and non-tree vertex.             ! ! Rutger Dijkstra and Mohamed GoudaDavid Gries and Vicki Almstrum planning the special issueInformation Processing Lette 1Chapter 4GreedySlides by Kevin WayneCopyright 2005 Pearson-Addison WesleyAll rights reserved44 Shortest Paths in a Graphshortest path from Princeton CS department to Einsteins house3Shortest Path P 1Chapter 4GreedySlides by Kevin WayneCopyright 2005 Pearson-Addison WesleyAll rights reserved44 Shortest Paths in a Graphshortest path from Princeton CS department to Einsteins house3Shortest Path P 1. NOTE: We may not get to Bellman-Ford! . We will spend more time on it next time.. Announcements. The midterm is over!. for most of you. Don’t talk about it just yet – we will tell you when it is ok to discuss the midterm!. Influence of Professor T. C. Hu’s Works on Fundamental Approaches in Layout. Andrew B. Kahng. CSE and ECE Departments. UC San Diego. http://vlsicad.ucsd.edu. Professor T. C. Hu. Introduced combinatorial optimization, and mathematical programming formulations and methods, to VLSI Layout.