Multi-leader migrating birds optimisation: a novel nature-inspired metaheuristic for combinatorial problems

Eduardo Lalla-Ruiz, Jesica de Armas, Christopher Exposito-Izquierdo, Belen Melian-Batista, J. Marcos Moreno-Vega

Research output: Contribution to journalArticleAcademicpeer-review

6 Citations (Scopus)


In this paper, we present multi-leader migrating birds optimisation. This algorithm is a nature-inspired population-based approach that exploits the concepts of self-organisation, cooperation, and distribution of migrating birds. For this purpose, the individuals maintain a well-defined relationship scheme. In this regard, each individual modifies a solution of the problem at hand through a set of operators defined by the user. The individuals cooperate among themselves during the search process by sharing information about the explored search space. Moreover, we assess the performance of our algorithm on the quadratic assignment problem due to the large number and heterogeneous characteristics of its application fields. The computational results disclose that the algorithm is highly competitive and provides new best solutions for the problem applied to printed circuit board problem.
Original languageEnglish
Pages (from-to)89-98
Number of pages10
JournalInternational Journal of Bio-Inspired Computation
Issue number2
Publication statusPublished - 2017
Externally publishedYes


  • nature-inspired
  • metaheuristic
  • migrating birds optimisation
  • MBO
  • n/a OA procedure


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