本文探讨了《算法导论》(CLRS)中关于图算法的部分，特别是第26章的最大流问题。作者分享了理解这些复杂概念的心得体会，强调了形成清晰的图模型的重要性，并指出这一部分更侧重于思维建模而非纯粹的数学推导。
Just finished reading Part 6, the graph algorithms. This part is kinda more fun, but of course more difficult – especially Ch. 26 “Max Flow”.
In my opinion Part 6 “Graph Algorithms” is more about “modeling” in your mind instead of deduction mental process as most of the former chapters. You have to form a quite clear graph model, and gain relatively clear concepts/restrictions in your mind, as the basic weapon for a further understanding of this part.
From Ch. 22 to Ch. 25, it is not that hard to understand what CLRS are talking about. The concepts from these chapters are some simple, and the many of the ideas are common. For example, several graph traversal strategies, and later on with the weight involved, it doesn’t get any more complex actually – nothing but involving some restrictions and the basic ideas are not changed.
While, things are getting interesting in Ch. 26. The concepts are a little difficult – it is not a static graph, it is a flowing pipeline network. So it is not only about constraints – they are working dynamically ! What is worth noticing is the mathematics is some different. There’re not so much abstruse pure “maths”, like some other chapters. More primary deduction techniques are applied – but they are no easier – these techniques are still tricky and subtle.
Anyway, you do need more time on this part.
Well, the last part is coming – “selected topics” – the most exciting chapters in the book I think, and I am really looking forward to enjoy them. I am coming :P
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