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courses:cs211:winter2014:journals:gabi:home [2014/04/02 01:12] – [Chapter 7.2] tremog | courses:cs211:winter2014:journals:gabi:home [2014/04/02 01:21] (current) – [Chapter 7.7] tremog | ||
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==== Chapter 7.7 ==== | ==== Chapter 7.7 ==== | ||
- | //**0.0: **// | + | //**7.7: Extensions to the Max-Flow Problem**// |
+ | **Summary: | ||
+ | Many issues that can be solved with the Max-Flow problem have essentially nothing to do with the fact that it models traffic in a network. Who knew? It also helps with problems that have nontrivial combinatorial search components. It is very useful because it can be solved in poly-time with O(Mc) time because of the F-F algorithm. | ||
- | **Summary:** | + | One of these problems is the :Circulations with demands: algorithm. For example, what if you had multiple sources and multiple sinks. In this problem, instead of maxing the flow value, we have to consider a problem in which the sources have fixed supply values and the sinks have fixed demands values and our job is to meet these demands. |
+ | (7:51) The Graph G has a feasible circulation with demands (dv) if and only if for all cuts (A,B) | ||
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+ | If all of the capacities and demands in G are integers and there is a feasible circulation, | ||
**Algorithms: | **Algorithms: | ||
+ | Once again, the F-F algorithm from section one. | ||
**Questions: | **Questions: | ||
+ | Where is the psudo-code? :( | ||
**What made sense?:** | **What made sense?:** | ||
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+ | The real world application. I don't know why but I can visualize this problem well. Maybe not real world, but this is much less of an abstraction than the ones in 7.5 and 7.2 | ||
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+ | **Key Points:** | ||
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+ | Many issues that can be solved with the Max-Flow problem have essentially nothing to do with the fact that it models traffic in a network. Who knew? | ||
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+ | **Readability (1-10):** | ||
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+ | 7. No psudeo-code :( | ||
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