Lecture 22 CSE 331 Oct 23, 2017.

Slides:



Advertisements
Similar presentations
Lecture 28 CSE 331 Nov 9, Flu and HW 6 Graded HW 6 at the END of the lecture If you have the flu, please stay home Contact me BEFORE you miss a.
Advertisements

Lecture 16 CSE 331 Oct 9, Announcements Hand in your HW4 Solutions to HW4 next week Remember next week I will not be here so.
Lecture 24 CSE 331 Oct 30, Homework stuff Please turn in your HW 6 Graded HW 5 and HW 7 at the END of the lecture.
Lecture 27 CSE 331 Nov 3, Combining groups Groups can unofficially combine in the lectures.
Lecture 39 CSE 331 Dec 9, Announcements Please fill in the online feedback form Sample final has been posted Graded HW 9 on Friday.
Lecture 25 CSE 331 Nov 2, Adding teeth to group talk Form groups of size at most six (6) Pick a group leader I will ask group leader(s) to come.
Lecture 27 CSE 331 Nov 6, Homework related stuff Solutions to HW 7 and HW 8 at the END of the lecture Turn in HW 7.
Using Dijkstra’s Algorithm to Find a Shortest Path from a to z 1.
Prof. Swarat Chaudhuri COMP 482: Design and Analysis of Algorithms Spring 2012 Lecture 10.
Week 4 Single Source Shortest Paths All Pairs Shortest Path Problem.
CSE 331: Review. Main Steps in Algorithm Design Problem Statement Algorithm Real world problem Problem Definition Precise mathematical def “Implementation”
Lecture 23 CSE 331 Oct 24, Reminder 2 points for Piazza participation 3 points for mini-project.
CSE 421 Algorithms Richard Anderson Lecture 8 Optimal Caching Dijkstra’s algorithm.
CSE 331: Review August 1, Main Steps in Algorithm Design Problem Statement Algorithm Real world problem Problem Definition Precise mathematical.
COMP108 Algorithmic Foundations Greedy methods
Graph Algorithms BFS, DFS, Dijkstra’s.
Lecture 15 CSE 331 Oct 3, 2016.
Lecture 23 CSE 331 Oct 26, 2016.
Lecture 15 CSE 331 Oct 3, 2016.
Lecture 21 CSE 331 Oct 21, 2016.
Lecture 24 CSE 331 Oct 28, 2016.
Lecture 24 CSE 331 Oct 27, 2017.
Greedy Algorithms / Dijkstra’s Algorithm Yin Tat Lee
Lecture 21 CSE 331 Oct 20, 2017.
Lecture 14 CSE 331 Sep 30, 2011.
Algorithms (2IL15) – Lecture 5 SINGLE-SOURCE SHORTEST PATHS
Lecture 37 CSE 331 Dec 1, 2017.
Shortest-Paths Trees Kun-Mao Chao (趙坤茂)
Lecture 13 CSE 331 Oct 1, 2012.
Lecture 24 CSE 331 Oct 25, 2013.
Lecture 26 CSE 331 Nov 1, 2017.
Richard Anderson Lecture 9 Dijkstra’s algorithm
Lecture 23 CSE 331 Oct 25, 2017.
Lecture 24 CSE 331 Oct 29, 2012.
Lecture 23 CSE 331 Oct 24, 2011.
Lecture 26 CSE 331 Nov 2, 2012.
Lecture 22 CSE 331 Oct 24, 2016.
Shortest Path Algorithms
Lecture 37 CSE 331 Nov 30, 2011.
Lecture 20 CSE 331 Oct 17, 2011.
Lecture 27 CSE 331 Oct 31, 2014.
Lecture 25 CSE 331 Oct 28, 2013.
Lecture 12 CSE 331 Sep 26, 2011.
Lecture 25 CSE 331 Oct 27, 2014.
Lecture 22 CSE 331 Oct 15, 2014.
Lecture 14 Shortest Path (cont’d) Minimum Spanning Tree
Lecture 11 CSE 331 Sep 19, 2014.
Chapter 24: Single-Source Shortest Paths
Lecture 24 CSE 331 Oct 24, 2014.
Weighted Graphs & Shortest Paths
Lecture 36 CSE 331 Nov 28, 2011.
Lecture 36 CSE 331 Nov 30, 2012.
Lecture 37 CSE 331 Dec 2, 2016.
Lecture 11 CSE 331 Sep 21, 2017.
Autumn 2016 Lecture 10 Minimum Spanning Trees
Lecture 12 CSE 331 Sep 22, 2014.
Lecture 23 CSE 331 Oct 24, 2011.
Winter 2019 Lecture 9 Dijkstra’s algorithm
Lecture 26 CSE 331 Nov 1, 2010.
Chapter 24: Single-Source Shortest Paths
CSE 417: Algorithms and Computational Complexity
Lecture 25 CSE 331 Oct 28, 2011.
Winter 2019 Lecture 10 Minimum Spanning Trees
Lecture 15 CSE 331 Oct 4, 2010.
Single-Source Shortest Path & Minimum Spanning Trees
Lecture 13 Shortest Path (cont’d) Minimum Spanning Tree
Data Structures and Algorithm Analysis Lecture 8
Lecture 36 CSE 331 Nov 22, 2013.
Lecture 24 CSE 331 Oct 29, 2018.
Autumn 2019 Lecture 9 Dijkstra’s algorithm
Presentation transcript:

Lecture 22 CSE 331 Oct 23, 2017

Graded mid-term-I Grades for mid-term-I released on Autolab mid-term 2 in a day or two

Temp letter grades

Today Shortest Path Problem http://xkcd.com/85/

Reading Assignment Sec 2.5 of [KT]

Shortest Path problem s 100 Input: Directed graph G=(V,E) w 15 5 s u w 100 Input: Directed graph G=(V,E) Edge lengths, le for e in E “start” vertex s in V 15 5 s u w 5 s u Output: All shortest paths from s to all nodes in V

Naïve Algorithm Ω(n!) time

Dijkstra’s shortest path algorithm E. W. Dijkstra (1930-2002)

Dijkstra’s shortest path algorithm 1 d’(w) = min e=(u,w) in E, u in R d(u)+le 1 2 4 3 y 4 3 u d(s) = 0 d(u) = 1 s x 2 4 d(w) = 2 d(x) = 2 d(y) = 3 d(z) = 4 w z 5 4 2 s w Input: Directed G=(V,E), le ≥ 0, s in V u R = {s}, d(s) =0 Shortest paths x While there is a x not in R with (u,x) in E, u in R z y Pick w that minimizes d’(w) Add w to R d(w) = d’(w)

Couple of remarks The Dijkstra’s algo does not explicitly compute the shortest paths Can maintain “shortest path tree” separately Dijkstra’s algorithm does not work with negative weights Left as an exercise