Given items with weight $w_i$ and profits $p_i$, minimization Knapsack problem is to pick a subset of items $I$, s.t. $\sum_{i\in{I}}{w_i} \geq W$ and $\sum_{i\in{I}}{p_i}$ is minimized.
The greedy algorithm simply sorts items based on ratio $\frac{p_i}{w_i}$. It scans and sum up the sorted items in increasing order, until $\sum{w_i}\geq{W}$. Then outputs $\sum{p_i}$.
If the distribution of $p_i$ is known (say, following zipf distribution) and $w_i$ is randomly distributed, and independently with value of $p_i$, then what is the average optimality ratio which is ratio of $\sum_{i\in{I}}{p_i}$ to the optimal results.
Note: in worst case, this greedy algorithm can be arbitrarily bad, according to following book. P412, Knapsack Problems, By Hans Kellerer, Ulrich Pferschy, David Pisinger.