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courses:cs211:winter2012:journals:paul:home [2012/04/06 01:44] – [Chapter 7] nguyenpcourses:cs211:winter2012:journals:paul:home [2012/04/06 02:10] – [Chapter 7] nguyenp
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       * Here's how we do it. We got a bunch of red and blue nodes. Add nodes s and t, which will be the start and end nodes. Have the start node s have a unit edge (edge of size 1) connect it to all the red nodes. Have all the blue nodes have a unit edge connect them to the end node t. Still have same edges in the middle.        * Here's how we do it. We got a bunch of red and blue nodes. Add nodes s and t, which will be the start and end nodes. Have the start node s have a unit edge (edge of size 1) connect it to all the red nodes. Have all the blue nodes have a unit edge connect them to the end node t. Still have same edges in the middle. 
       * Now, use same algorithm as in the first section. BOOOM!!! Right? Yep. It's pretty intuitive, these later sections are more like practical uses rather than actual algorithms. I guess this is kind of good since pretty much all computer science problems go back to graph theory.        * Now, use same algorithm as in the first section. BOOOM!!! Right? Yep. It's pretty intuitive, these later sections are more like practical uses rather than actual algorithms. I guess this is kind of good since pretty much all computer science problems go back to graph theory. 
-      * +      * Extensions: The structore of bipartite graphs with no perfect matching 
 +          * Dicusses how to tell if it is impossible to find a perfect matching in a bipartite graph.  
 +          * Can easily find an algorithm based on the following theorem: 
 +              * Assume that the bipartite graph G=(V,E) has two sides X and Y such that |X| and |Y|. Then the graph G either has a perfect matching or these is a subset A such that |\G(A)|<|A|. A perfect matching or an appropriate subset A can be found in O(mn) time.  
 +  * Section 7.7 - Extensions to Max-Flow Problem 
 +      * Circulations with Demands 
 +          * We have a directed graph 
 +          * edges have capacities 
 +          * nodes have supply and demands 
 +          * A circulation is a function that satisfies the following 
 +              * the flows for a particular edge are always less than the capacity (makes sense and is very intuitive) 
 +              * the demand for a node is equal to the stuff coming in minnus the stuff going out (the the demand that his node has? I guess that makes enough sense...) 
 +          * To keep the world form exploding, the sum of supplies == sum of demands 
 +          * Algorithm: more details on pg 381 and 382 
 +              * Add a new source s and sink t 
 +              * For each v with d(v) < 0, add edge (s, v) with capacity -d(v) 
 +              * For each v with d(v) > 0, add edge (v, t) with capacity d(v) 
 +          * MAGIC: G has circulation iff G' has max flow of value D 
 +          * MORE MAGIC : Given (V, E, c, d), there does not exist a circulation iff there exists a node partition (A, B) such that the sum of all the demands is greater than cap(A,B) 
 +          * These two pretty much solve the problem for us.  more details are on page 382 if you get confused rereading this sometime in the future 
 +          
courses/cs211/winter2012/journals/paul/home.txt · Last modified: 2012/04/06 02:17 by nguyenp
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