This is the same idea behind binary search. In a sorted array, you compare against the middle element and eliminate half the remaining candidates. In a quadtree, you choose one of four quadrants and ignore the other three regions. Each level narrows the search space by a factor of four instead of two.
We wanted a scenario where, say, 5 well-placed border points could efficiently represent an area with 5,000 internal points and 10,000 road edges. This would reduce those 10,000 edges to just 5*4/2 = 10 shortcuts for routing through that cluster at a high level – an incredible 1:1000 point ratio and a 30x reduction in edges to consider for the high-level path!
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16:09, 27 февраля 2026Экономика