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cs-312:hw20.5 [2014/12/31 16:22]
ringger
cs-312:hw20.5 [2015/03/07 17:52] (current)
ringger [Question 2]
Line 7: Line 7:
 7.10 in the textbook 7.10 in the textbook
  
-Pages 203 and 204 in the printed textbook will be useful in understanding what is required for finding the smallest (i.e., minimum capacity) (s-t)-cut that matches the maximum flow.+Pages 203 and 204 in the printed textbook will be useful in understanding what is required for finding the smallest (i.e., minimum capacity) ​$(s-t)$-cut that matches the maximum flow.
  
-TODO: add pages for online textbook. 
  
 === Question 2 === === Question 2 ===
 Linear Programming and the Maximum Flow Problem: ​ Consider the directed graph $G=(E,​V)$. ​ Without loss of generality, let $s$ be the source vertex and $t$ be the sink vertex in $V$. For each edge $(u,v)\in E$, let $c_{uv}$ denote the capacity of that edge. Now, formulate the '''​general'''​ maximum flow problem (not a specific instance) as a linear programming problem as follows: Linear Programming and the Maximum Flow Problem: ​ Consider the directed graph $G=(E,​V)$. ​ Without loss of generality, let $s$ be the source vertex and $t$ be the sink vertex in $V$. For each edge $(u,v)\in E$, let $c_{uv}$ denote the capacity of that edge. Now, formulate the '''​general'''​ maximum flow problem (not a specific instance) as a linear programming problem as follows:
-(a) First, define the variables. +(a) First, define the variables. ​ (I recommend representing the flows through each edge as your variables.) 
-(b) Second, use those variables to formulate all of the necessary elements of a linear program in algebraic terms, and make sure that your formulation is in standard form up to step #1.+(b) Second, use those variables to formulate all of the necessary elements ​(i.e., objective function and constraints) ​of a linear program in algebraic terms.
  
cs-312/hw20.5.1420068178.txt.gz · Last modified: 2014/12/31 16:22 by ringger
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