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Related Concept Videos

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Related Experiment Videos

Efficiently finding earliest and latest paths via binary weighting in multi-objective network routing.

Wei-Chang Yeh1, Majid Forghani-Elahabad2, Amit Kumar3

  • 1Department of Industrial Engineering and Engineering Management, National Tsing Hua University, Hsinchu, Taiwan, Department of Industrial and Systems Engineering, Chung Yuan Christian University, Taoyuan, Taiwan.

Scientific Reports
|May 7, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces novel earliest and latest path algorithms using binary arc weights. These methods efficiently identify network paths, improving routing efficiency and reliability in complex systems.

Keywords:
Binary WeightDijkstra’s algorithmEarliest/Latest PathFlow Networks

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Area of Science:

  • Computer Science
  • Network Algorithms
  • Graph Theory

Background:

  • Traditional shortest-path algorithms often focus solely on distance.
  • Multi-objective routing in complex networks presents computational challenges.
  • Efficient path selection is crucial for network reliability and performance.

Purpose of the Study:

  • To develop new path-selection algorithms (earliest and latest path) using binary arc weights.
  • To enable retrieval of paths based on lexicographical order for minimal/maximal representations.
  • To offer a richer path representation than standard shortest-path formulations.

Main Methods:

  • Assigning binary weights (2^(i-1) or 2^(m-i)) to network arcs.
  • Utilizing a binary addition tree ordering for path analysis.
  • Implicitly dividing path space into disconnected, potentially connected, and impossible paths.

Main Results:

  • The proposed algorithms achieve O((|V|+|E|)log|V|) time complexity, similar to Dijkstra's.
  • A richer path representation is achieved compared to standard shortest-path methods.
  • Significant reduction in computation time compared to classical multi-objective routing.

Conclusions:

  • The new algorithms provide an efficient and comprehensive approach to path selection.
  • The method enhances system reliability and facilitates quick, relevant path identification.
  • Applicable to diverse real-world networks including communications, transportation, and logistics.