Central European Journal of Operations Research

, Volume 19, Issue 4, pp 445–466

Similarities between meta-heuristics algorithms and the science of life

Original Paper

DOI: 10.1007/s10100-010-0135-x

Cite this article as:
Ruiz-Vanoye, J.A. & Díaz-Parra, O. Cent Eur J Oper Res (2011) 19: 445. doi:10.1007/s10100-010-0135-x


In this paper, we show the functional similarities between Meta-heuristics and the aspects of the science of life (biology): (a) Meta-heuristics based on gene transfer: Genetic algorithms (natural evolution of genes in an organic population), Transgenic Algorithm (transfers of genetic material to another cell that is not descending); (b) Meta-heuristics based on interactions among individual insects: Ant Colony Optimization (on interactions among individuals insects, Ant Colonies), Firefly algorithm (fireflies of the family Lampyridze), Marriage in honey bees Optimization algorithm (the process of reproduction of Honey Bees), Artificial Bee Colony algorithm (the process of recollection of Honey Bees); and (c) Meta-heuristics based on biological aspects of alive beings: Tabu Search Algorithm (Classical Conditioning on alive beings), Simulated Annealing algorithm (temperature control of spiders), Particle Swarm Optimization algorithm (social behavior and movement dynamics of birds and fish) and Artificial Immune System (immunological mechanism of the vertebrates).


Biological similarity Bio-inspired algorithms Meta-heuristic algorithms 


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Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  1. 1.Centro Nacional de Investigación y Desarrollo TecnológicoCuernavacaMexico
  2. 2.Universidad Autónoma del Estado de Morelos. FCAeICuernavacaMexico

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