Analytics Magazine Analytics Magazine, March/April 2014 | Page 73

Figure 1: A Standard Lego brick, measuring 8 mm square (1LC in this article’s measurements), with a standard U.S. quarter and Darth Vader for size comparison. Figure 2: Lego promotional brickbox (left) and for-purchase brickbox cup (right). Which holds more? to simulate. It is possible, for small problems, to simulate the system itself, which entails actual Legos, actual children and an actual box. And here’s where I stopped being in control and the problem took over. I went to the store and purchased a (non-promotional) Lego brickbox. This one is different than the promotional version, because it is a large round cup, and now things get really interesting. Because while packing square Legos in a square box is easy, packing square Legos in a round cup is hard. My idea was to have a set of Lego bricks, 1x1, 1x4, 2x2 and 2x4 of different colors for a group of children to toss into the promotional (square) box. We could then determine what an “average” random fill of bricks might be. I didn’t concern myself too much with optimally packing the cup; I reasoned that it was so much larger than the box (946 vs. 670 cubic centimeters) that I wouldn’t need to worry too much about optimizing. Naïvely, based solely on volume, one might estimate that the large cup holds 1,678 bricks. This is a naïve measure because it simply divides the volume of the box by the volume of the bricks. I turned out to be dead wrong; my brick purchase that haphazardly filled the cup only filled the box (when optimally stacked) a little more than half way! This is because it’s difficult to pack squares into a round container, even more so when you don’t try. M A R C H / A P R I L 2 014 | 73