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A Fast and Simple Algorithm for the Resource Constrained Shortest Path Problem

Authors Saman Ahmadi , Andrea Raith , Mahdi Jalili

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ACM Subject Classification
  • Computing methodologies → Search methodologies
  • Theory of computation → Shortest paths
Keywords
  • constrained pathfinding
  • shortest path problem
  • heuristic search

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Abstract

Constrained pathfinding is a classic yet challenging network optimization problem with broad applicability across many real-world domains. The Resource-Constrained Shortest Path (RCSP) problem focuses on finding cost-optimal paths that satisfy multiple resource constraints. In this paper, we propose a novel heuristic-guided search framework that accelerates constrained search in large-scale networks, including those with negative costs and resources, by leveraging efficient queuing and pruning strategies. Experimental results on real-world benchmark maps show that our framework achieves up to two orders of magnitude speedup over state-of-the-art methods, demonstrating its effectiveness in solving challenging RCSP instances within limited time.

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Saman Ahmadi, Andrea Raith, and Mahdi Jalili. A Fast and Simple Algorithm for the Resource Constrained Shortest Path Problem. In 33rd Annual European Symposium on Algorithms (ESA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 351, pp. 97:1-97:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025) https://doi.org/10.4230/LIPIcs.ESA.2025.97

Author Details

Saman Ahmadi
  • School of Engineering, RMIT University, Melbourne, Australia
Andrea Raith
  • Department of Engineering Science, University of Auckland, New Zealand
Mahdi Jalili
  • School of Engineering, RMIT University, Melbourne, Australia

Funding

This research was supported by the Department of Climate Change, Energy, the Environment and Water under the International Clean Innovation Researcher Networks (ICIRN) program grant number ICIRN000077. Mahdi Jalili is supported by Australian Research Council through projects DP240100963, DP240100830, LP230100439 and IM240100042.

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