Combining Tabu search and genetic algorithms to solve the capacitated multicommodity network flow problem

Carolina Lagos, BRODERICK CRAWFORD LABRIN, Enrique Cabrera, RICARDO JAVIER SOTO DE GIORGIS, Jose Miguel Rubio, Fernando Paredes

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Network design has been an important issue in logistics during the last century. This is due to the significant impact that an efficient distribution network design can have over both costs and service level. In this article, we present a heuristic solution approach for the well-known capacitated multicommodity network flow problem. The heuristic approach combines two well-known algorithms namely Tabu Search and Genetic Algorithms. While the main algorithm is Tabu Search, the Genetic Algorithm is used to select the best option among the neighbours of the current solution. To be able to do that some well-known evolutionary operators such as cross-over and mutation are made use of. This hybrid approach obtains important improvements when compared to the ones presented previously in the literature.

Original languageEnglish
Pages (from-to)265-276
Number of pages12
JournalStudies in Informatics and Control
Volume23
Issue number3
DOIs
StatePublished - 1 Jan 2014

Keywords

  • Genetic algorithms
  • Multicommodity network flow problem
  • Network design
  • Probabilistic neighbour selection criterion
  • Tabu search

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