The Ant Colony Optimization Metaheuristic : Algorithms , Applications , and Advances

  title={The Ant Colony Optimization Metaheuristic : Algorithms , Applications , and Advances},
  author={Marco Dorigo and Franklin D. Roosevelt},
Ant Colony Optimization (ACO) [31, 32] is a recently propose d metaheuristic approach for solving hard combinatorial optimization proble ms. The inspiring source of ACO is the pheromone trail laying and following behavior o f eal ants which use pheromones as a communication medium. In analogy to the biol ogical example, ACO is based on the indirect communication of a colony of simp le agents, called (artificial) ants, mediated by (artificial) pheromone trail s. The pheromone trails in ACO serve… CONTINUE READING
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Publications referenced by this paper.
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The MAX–MIN Ant System and local search for the traveling salesman problem

  • T. Stützle, H. H. Hoos
  • editors,Proceedings of the 1997 IEEE…
  • 1997
Highly Influential
13 Excerpts

Optimization, Learning and Natural Algorithms (in Italian)

  • M. Dorigo
  • PhD thesis, Dipartimento di Elettronica…
  • 1992
Highly Influential
4 Excerpts

A short convergence proof for a class of ACO algorithms

  • T. Stützle, H. H. Hoos
  • IEEE Transactions on Evolutionary Computation
  • 2002

Abstract proceedings of ANTS2000 – From Ant Colonies to Artificial Ants: A Series of In ter ational Workshops on Ant Algorithms

  • M. Dorigo, M. Middendorf, T. Stützle, editors
  • Libre de Bruxelles,
  • 2000
1 Excerpt

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