Data-driven Floyd’s algorithm with AirQo monitoring device for optimizing transportation routes in an uncertain environment


Vimala J., Ashma Banu K., Kausar N., PAMUCAR D., Simic V.

Engineering Applications of Artificial Intelligence, vol.163, 2026 (SCI-Expanded, Scopus) identifier identifier

  • Nəşrin Növü: Article / Article
  • Cild: 163
  • Nəşr tarixi: 2026
  • Doi nömrəsi: 10.1016/j.engappai.2025.113134
  • jurnalın adı: Engineering Applications of Artificial Intelligence
  • Jurnalın baxıldığı indekslər: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, INSPEC
  • Açar sözlər: Air pollution, AirQo monitoring device, All-Pair Shortest Path, Complex Fuzzy set, Floyd’s algorithm
  • Açıq Arxiv Kolleksiyası: Məqalə
  • Adres: Bəli

Qısa məlumat

This manuscript presents a novel All-pair shortest path algorithm that enhances Floyd’s method by integrating a soft computing-based decision model tailored for transportation routing in an uncertain environment. The routing problem is formulated as a graph, where the edges are aggregated into a single representative weight from multiple influencing factors using an aggregation operator and the score function. These weights represent pollution levels based on air quality data collected by the AirQo monitoring device along different route segments. By integrating decision making method, the enhanced Floyd’s algorithm is then used to compute the most effective route between a defined source and destination. The proposed method supports healthier travel choices by identifying routes with comparatively cleaner air. Preliminary simulations indicate that the suggested technique facilitates more informed route selection compared to conventional approaches. The uniqueness of this method lies in its integration of classical graph theory with decision-making for real-time environmental sensing, offering reduced exposure to pollutants and supporting cleaner, safer mobility in urban environments.