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

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.