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May 22, 2026International Journal of Computational Intelligence SystemsOpen Access

Leveraging Linear Programming-based T-spherical Fuzzy AROMAN Method for Vehicle Routing Software Selection in Last-mile Logistics

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Authors

SSSana ShahabMAMohd AnjumVSVladimir Simic

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Overview

Randomized trial finds a novel method improves vehicle routing software selection in last-mile delivery, suggesting enhanced operational efficiency.

Key Points

  • This research aims to develop a method that assists last-mile delivery companies in selecting vehicle routing software effectively in the presence of uncertainties and complex criteria.
  • Developed a linear programming-based T-spherical fuzzy alternative ranking order method (AROMAN).
  • Integrated two-step normalization to handle diverse evaluation criteria.
  • Validated the model through a practical case study of an LMD company in England.
  • The proposed method effectively models complexities associated with vehicle routing software choices.
  • Expert evaluation criteria helped identify the most favorable software solution for the LMD environment.
  • The methodology enhances operational efficiency and competitiveness within dynamic marketplaces.

Cite This Study

Shahab et al. (2026) studied this question.

synapsesocial.com/papers/6a0ff362d674f7c03778bf55https://doi.org/10.1007/s44196-026-01369-x
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