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A Fuzzy Tabu Search Approach to Solve a Vehicle Routing Problem

Kaj-Mikael Björk, József Mezei, A Fuzzy Tabu Search Approach to Solve a Vehicle Routing Problem. In: Ignacio Rojas, Gonzalo Joya, Joan Gabestany (Eds.), Advances in Computational Intelligence, Lecture Notes in Computer Science, 210–217, Springer, 2013.


In this paper, we develop a framework to solve a multi-objective fuzzy vehicle routing problem. The decision variables in the problem are found in the routing decisions and the determination of the pickup order for a set of loads and available trucks. The objective to minimize is both the total time and distance traveled by all the vehicles. The uncertainty in the model is inspired from a timber transportation context, where times are, and sometimes even distances, uncertain. Because of lack of statistical data the uncertainties are sometimes best described as fuzzy numbers. The model developed is solved with a tabu search method, allowing for the above mentioned uncertainties. Finally, the framework is also illustrated with a numerical example.

BibTeX entry:

  title = {A Fuzzy Tabu Search Approach to Solve a Vehicle Routing Problem},
  booktitle = {Advances in Computational Intelligence},
  author = {Björk, Kaj-Mikael and Mezei, József},
  series = {Lecture Notes in Computer Science},
  editor = {Rojas, Ignacio and Joya, Gonzalo and Gabestany, Joan},
  publisher = {Springer},
  pages = {210–217},
  year = {2013},

Belongs to TUCS Research Unit(s): Institute for Advanced Management Systems Research (IAMSR)

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