Comparing Search Algorithms Using Sorting and Hashing on Disk and in Memory / 610
Richard E. Korf
We compare sorting and hashing for implicit graph search using disk storage. We first describe efficient pipelined implementations of both algorithms, which reduce disk I/O. We then compare the two algorithms and find that hashing is faster, but that sorting requires less disk storage. We also compare disk-based with in-memory search, and surprisingly find that there is little or no time overhead associated with disk-based search. We present experimental results on the sliding-tile puzzles, Rubik's Cube, and the 4-peg Towers of Hanoi.