Resource Constrained Pathfinding with Enhanced Bidirectional A* Search

Saman Ahmadi, Andrea Raith, Guido Tack, Mahdi Jalili
12/18/2024
cs.AI

No confident code implementation found for this paper.

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.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. Any repos shown below are weak matches — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Cite this paper

@article{ahmadi2024resource,
  title  = {Resource Constrained Pathfinding with Enhanced Bidirectional A* Search},
  author = {Saman Ahmadi and Andrea Raith and Guido Tack and Mahdi Jalili},
  year   = {2024},
  eprint = {2412.13888},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2412.13888v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2412.13888.svg)](https://codeofpaper.com/paper/2412.13888)

Discussion