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Mixed steepest descent algorithm for the traveling salesman problem and application in air logistics

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  • Muren,
  • Wu, Jianjun
  • Zhou, Li
  • Du, Zhiping
  • Lv, Ying

Abstract

In this paper, a new mixed steepest descent algorithm which has short computation time and stable solution is provided. Comparisons and case studies based on different traffic network and distance are made with other intelligent and exact algorithms. The large-scale experiment shows that the possibility of securing the optimal solution is greater than 99.5% and the average computation time is lower than 0.06 s when the node scales are less than 50. The proposed algorithm can not only be applied in emergency logistics problems but is also useful for solving other real-world problems.

Suggested Citation

  • Muren, & Wu, Jianjun & Zhou, Li & Du, Zhiping & Lv, Ying, 2019. "Mixed steepest descent algorithm for the traveling salesman problem and application in air logistics," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 126(C), pages 87-102.
    • Handle: RePEc:eee:transe:v:126:y:2019:i:c:p:87-102
    DOI: 10.1016/j.tre.2019.04.004
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    3. Scianna, Marco, 2024. "The AddACO: A bio-inspired modified version of the ant colony optimization algorithm to solve travel salesman problems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 218(C), pages 357-382.

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