Synonyms
Definition
Ant colony optimization (ACO) is a population-based metaheuristic for the solution of difficult combinatorial optimization problems. In ACO, each individual of the population is an artificial agent that builds incrementally and stochastically a solution to the considered problem. Agents build solutions by moving on a graph-based representation of the problem. At each step their moves define which solution components are added to the solution under construction. A probabilistic model is associated with the graph and is used to bias the agents’ choices. The probabilistic model is updated on-line by the agents so as to increase the probability that future agents will build good solutions.
Motivation and Background
Ant colony optimization is so called because of its original inspiration: the foraging behavior of some ant species. In particular, in Beckers et al. (1992) it was demonstrated experimentally that ants are able to find the shortest path between their...
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Recommended Reading
Beckers R, Deneubourg JL, Goss S (1992) Trails and U-turns in the selection of the shortest path by the ant Lasius Niger. J Theor Biol 159:397–415
Dorigo M, Gambardella LM (1997) Ant colony system: a cooperative learning approach to the traveling salesman problem. IEEE Trans Evol Comput 1(1):53–66
Dorigo M, Stützle T (2004) Ant colony optimization. MIT Press, Cambridge
Dorigo M, Maniezzo V, Colorni A (1991) Positive feedback as a search strategy. Technical report 91-016, Dipartimento di Elettronica, Politecnico di Milano, Milan
Dorigo M, Maniezzo V, Colorni A (1996) Ant system: optimization by a colony of cooperating agents. IEEE Trans Syst Man Cybern – Part B 26(1): 29–41
Maniezzo V (1999) Exact and approximate nondeterministic tree-search procedures for the quadratic assignment problem. INFORMS J Comput 11(4):358–369
Stützle T, Hoos HH (1997) The \(\mathcal{M}AX -\mathcal{M}IN\) ant system and local search for the traveling salesman problem. In: Proceedings of the 1997 congress on evolutionary computation – CEC’97. IEEE Press, Piscataway, pp 309–314
Stützle T, Hoos HH (2000) \(\mathcal{M}AX -\mathcal{M}IN\) ant system. Future Gener Comput Syst 16(8):889–914
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer Science+Business Media New York
About this entry
Cite this entry
Dorigo, M., Birattari, M. (2017). Ant Colony Optimization. In: Sammut, C., Webb, G.I. (eds) Encyclopedia of Machine Learning and Data Mining. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-7687-1_22
Download citation
DOI: https://doi.org/10.1007/978-1-4899-7687-1_22
Published:
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4899-7685-7
Online ISBN: 978-1-4899-7687-1
eBook Packages: Computer ScienceReference Module Computer Science and Engineering