Chapter 11. Hard Problems and (Limited) Sloppiness


The best is the enemy of the good.


This book is clearly about algorithmic problem solving. Until now, the focus has been on basic principles for algorithm design, as well as examples of important algorithms in many problem domains. Now, I'll give you a peek at the flip side of algorithmics: hardness. Although it is certainly possible to find efficient algorithms for many important and interesting problems, the sad truth is that most problems are really hard. In fact, most are so hard that there's little point in even trying to solve them. It then becomes important to recognize hardness, to show that a problem is intractable (or at least very likely so), and to know what alternatives ...

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