Resource Constrained Pathfinding with Enhanced Bidirectional A* Search
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.
Cite
@article{arxiv.2412.13888,
title = {Resource Constrained Pathfinding with Enhanced Bidirectional A* Search},
author = {Saman Ahmadi and Andrea Raith and Guido Tack and Mahdi Jalili},
journal= {arXiv preprint arXiv:2412.13888},
year = {2025}
}
Comments
9 pages, 3 figures, 2 tables, The 39th Annual AAAI Conference on Artificial Intelligence