Algorithms For Dummies

 Challenging Difficult Problems

problem consists of known examples or because the problem is compatible with 

matroid mathematical framework. Even when a greedy algorithm works best in 

one  setting,  changing  the  setting  may  break the toy  and  generate  just  good  or 

acceptable solutions. In fact, the cases of just good or acceptable results are many, 

because greedy algorithms don’t often outperform other solutions, as shown by

 

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The make-change problem solutions demonstrated earlier in this chapter 

show how a change in setting can cause a greedy algorithm to stop working.

 

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The scheduling problem (described in the “Finding Out How Greedy Can Be 

Useful” section, later in this chapter) illustrates how a greedy solution works 

perfectly with one worker, but don’t expect it to work with more than one.