Heuristics: intelligent search strategies for computer problem solving
Heuristics: intelligent search strategies for computer problem solving
Fibonacci heaps and their uses in improved network optimization algorithms
Journal of the ACM (JACM)
BS*: an admissible bidirectional staged heuristic search algorithm
Artificial Intelligence
Computer graphics (2nd ed. in C): principles and practice
Computer graphics (2nd ed. in C): principles and practice
Approximation algorithms for the geometric covering salesman problem
Discrete Applied Mathematics
Algorithms for Searching Massive Graphs
IEEE Transactions on Knowledge and Data Engineering
An Efficient Path Computation Model for Hierarchically Structured Topographical Road Maps
IEEE Transactions on Knowledge and Data Engineering
Modelling a Hierarchy of Space Applied to Large Road Networks
IGIS '94 Proceedings of the International Workshop on Advanced Information Systems: Geographic Information Systems
Using Multi-level Graphs for Timetable Information in Railway Systems
ALENEX '02 Revised Papers from the 4th International Workshop on Algorithm Engineering and Experiments
Shortest Path Algorithms: An Evaluation Using Real Road Networks
Transportation Science
Touring a sequence of polygons
Proceedings of the thirty-fifth annual ACM symposium on Theory of computing
Compact oracles for reachability and approximate distances in planar digraphs
Journal of the ACM (JACM)
Computing the shortest path: A search meets graph theory
SODA '05 Proceedings of the sixteenth annual ACM-SIAM symposium on Discrete algorithms
Planar graphs, negative weight edges, shortest paths, and near linear time
Journal of Computer and System Sciences - Special issue on FOCS 2001
Highway hierarchies hasten exact shortest path queries
ESA'05 Proceedings of the 13th annual European conference on Algorithms
| Hi-index | 0.00 |
Today's map navigation software offers more and more functionality. For example, it cannot only route from a start to a destination address, but the user can also specify a number of via destinations that are to be visited along the route. What is not commonly found in the software is the handling of so-called stopover areas. Here the user specifies a sequence of geographic areas and wants the route to lead into or through each of these areas (but he does not actually care where exactly). A modification of the well-known A☆ algorithm that considers convex stopover areas is presented. Algorithmic variants and implementation issues are discussed. Example results on a real-world data set are presented for the case of axis parallel rectangular stopover areas.