Resource Constrained Pathfinding with Enhanced Bidirectional A* Search
December 18, 2024 Β· Declared Dead Β· π AAAI Conference on Artificial Intelligence
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Authors
Saman Ahmadi, Andrea Raith, Guido Tack, Mahdi Jalili
arXiv ID
2412.13888
Category
cs.AI: Artificial Intelligence
Citations
1
Venue
AAAI Conference on Artificial Intelligence
Last Checked
4 months ago
Abstract
The classic Resource Constrained Shortest Path (RCSP) problem aims to find a cost optimal path between a pair of nodes in a network such that the resources used in the path are within a given limit. Having been studied for over a decade, RCSP has seen recent solutions that utilize heuristic-guided search to solve the constrained problem faster. Building upon the bidirectional A* search paradigm, this research introduces a novel constrained search framework that uses efficient pruning strategies to allow for accelerated and effective RCSP search in large-scale networks. Results show that, compared to the state of the art, our enhanced framework can significantly reduce the constrained search time, achieving speed-ups of over to two orders of magnitude.
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