Localizing A*

Heuristic search in large problem spaces inherently calls for algorithms capable of running under restricted memory. This question has been investigated in a number of articles. However, in general the e cient usage of two-layered storage systems is not further discussed. Even if hard-disk capacity is su cient for the problem instance at hand, the limitation of main memory may still represent the bottleneck for their practical applications. Since breadthrst and bestrst strategies do not exhibit any locality of expansion, standard virtual memory management can soon result in thrashing due to excessive page faults. In this paper we propose a new search algorithm and suitable data structures in order to minimize page faults by a local reordering of the sequence of expansions. We prove its correctness and completeness and evaluate it in a real-world scenario of searching a large road map in a commercial route planning system.