A Survey of Shortest-Path Algorithms
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Abstract (arXiv)
A shortest-path algorithm finds a path containing the minimal cost between two vertices in a graph. A plethora of shortest-path algorithms is studied in the literature that span across multiple disciplines. This paper presents a survey of shortest-path algorithms based on a taxonomy that is introduced in the paper. One dimension of this taxonomy is the various flavors of the shortest-path problem. There is no one general algorithm that is capable of solving all variants of the shortest-path problem due to the space and time complexities associated with each algorithm. Other important dimensions of the taxonomy include whether the shortest-path algorithm operates over a static or a dynamic graph, whether the shortest-path algorithm produces exact or approximate answers, and whether the objective of the shortest-path algorithm is to achieve time-dependence or is to only be goal directed. This survey studies and classifies shortest-path algorithms according to the proposed taxonomy. The survey also presents the challenges and proposed solutions associated with each category in the taxonomy.
Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). First posted on arXiv 4 May 2017.
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Citing papers per year: 2021: 1; 2022: 1; 2023: 1; 2024: 1; 2025: 2; 2026: 4.
10 papers.
- 2026Learning Shortest Paths with Generative Flow Networkscited by 2
- 2021An Extension of BIM Using AI: a Multi Working-Machines Pathfinding Solutioncited by 1
- 2022Deep Recurrent Q-learning for Energy-constrained Coverage with a Mobile Robotcited by 1
- 2026An Empirical Survey and Benchmark of Learned Distance Indexes for Road Networkscited by 1
- 2026GraphDC: A Divide-and-Conquer Multi-Agent System for Scalable Graph Algorithm Reasoningcited by 1
- 2023ERA*: Enhanced Relaxed A* algorithm for Solving the Shortest Path Problem in Regular Grid Mapscited by 0
- 2024Reciprocal Visibilitycited by 0
- 2025Skeleton-Guided Learning for Shortest Path Searchcited by 0
- 2025Predictive Spike Timing Enables Distributed Shortest Path Computation in Spiking Neural Networkscited by 0
- 2026Graph Instance Landscapes: When Structural Similarity Does (Not) Reflect Shortest-Path Performancecited by 0
- 2026Graph Instance Landscapes: When Structural Similarity Does (Not) Reflect Shortest-Path Performance1 Jun 2026
- 2026GraphDC: A Divide-and-Conquer Multi-Agent System for Scalable Graph Algorithm Reasoning18 Apr 2026
- 2026Learning Shortest Paths with Generative Flow Networks2 Mar 2026
- 2026An Empirical Survey and Benchmark of Learned Distance Indexes for Road Networks3 Feb 2026
- 2025Predictive Spike Timing Enables Distributed Shortest Path Computation in Spiking Neural Networks12 Sep 2025
- 2025Skeleton-Guided Learning for Shortest Path Search4 Aug 2025
- 2024Reciprocal Visibility10 Feb 2024
- 2023ERA*: Enhanced Relaxed A* algorithm for Solving the Shortest Path Problem in Regular Grid Maps15 Aug 2023
- 2022Deep Recurrent Q-learning for Energy-constrained Coverage with a Mobile Robot1 Oct 2022
- 2021An Extension of BIM Using AI: a Multi Working-Machines Pathfinding Solution14 May 2021