Provable Efficiency of Contraction Hierarchies with Randomized Preprocessing

We present a new way of analyzing Contraction Hierarchies (CH), a widely used speed-up technique for shortest path computations in road networks. In previous work, preprocessing and query times of deterministically constructed CH on road networks with n nodes were shown to be polynomial in n as well as the highway dimension h of the network and its diameter D. While h is conjectured to be polylogarithmic for road networks, a tight bound remains an open problem. We rely on the empirically justifiable assumption of the road network exhibiting small growth. We introduce a method to construct randomized Contraction Hierarchies on road networks as well as a probabilistic query routine. Our analysis reveals that randomized CH lead to sublinear search space sizes in the order of √ n log √ n, auxiliary data in the order of n log √ n, and correct query results with high probability after a polynomial time preprocessing phase.