In a geographical route search, given search terms, the goal is to find an effective route that (1) starts at a given location, (2) ends at a given location, and (3) travels via geographical entities that are relevant to the given terms. A route is effective if it does not exceed a given distance limit whereas the ranking scores of the visited entities, with respect to the search terms, are maximal. This paper introduces route-search queries, suggests three semantics for such queries and deals with the problem of efficiently answering queries under the different semantics. Since the problem of answering route-search queries is a generalization of the traveling salesman problem, it is unlikely to have an efficient solution, i.e., there is no polynomial-time algorithm that solves the problem (unless P=NP). Hence, in this work we consider heuristics for the problem. Methods for effectively computing routes are presented. The methods are compared analytically and experimentally. For these methods, experiments on both synthetic and real-world data illustrate their efficiency and their effectiveness in computing a route that satisfies the constraints of a route-search query.
Kanza et al. REF have shown polynomial-time heuristics for the constrained version of the TPQ problem.
Heuristic algorithms for route-search queries over geographical data
GIS '08
Computer Science