M. Dorigo, T. Stützle, Ant Colony Optimization: Overview and Recent Advances.
M. Gendreau and Y. Potvin, editors, Handbook of Metaheuristics, 2nd edition. Vol. 146 in International Series in Operations Research & Management Science, pp. 227--263. Springer, Verlag, New York, 2010.
M. Dorigo, M. Birattari, T. Stützle, Ant Colony Optimization--
Artificial Ants as a Computational Intelligence Technique, IEEE Computational Intelligence Magazine, 2006. IridiaTr2006-023r001.pdf
Short and concise
M. Dorigo & K. Socha, An Introduction to Ant Colony Optimization. T. F. Gonzalez (Ed.), Approximation Algorithms and Metaheuristics, CRC Press, 2007. IridiaTr2006-010r003.pdf
O. Cordon, F. Herrera, and T. Stützle,
A Review on the Ant Colony Optimization Metaheuristic: Basis, Models and New Trends. Mathware and Soft Computing, 9(2-3),
pp. 141--175, 2002. MSC-Intro-prel.ps.gz
M. Dorigo and G. Di Caro,
The Ant Colony Optimization Meta-Heuristic. In D. Corne, M. Dorigo and F. Glover, editors, New
Ideas in Optimization, McGraw-Hill, 11-32,1999. OptBook.ps.gz
M. Dorigo, G. Di Caro and L. M. Gambardella, Ant Algorithms
for Discrete Optimization. Artificial Life, 5(2):137-172, 1999. IJ.23-alife99.pdf
Much of the early research in ACO has focused on the development of
algorithmic variants that improve in performance over the original
Ant System algorithm. Here, we give the references to the main
articles describing the various variants of ACO algorithm. The publication dates of the given articles do not necessarily correspond to the temporal order in which the variants have
been proposed. (For a chronological development see ACO history.)
Ant System
M. Dorigo, V. Maniezzo & A. Colorni, Ant System: Optimization by a colony of cooperating agents.
IEEE Transactions on Systems, Man, and Cybernetics-Part B, 26(1):29-41,1996. IJ.10-SMC96.pdf
Elitist Ant System
M. Dorigo, Optimization, Learning and Natural Algorithms. Ph.D.Thesis, Politecnico di Milano, Italy, [in Italian], 1992.; M.Dorigo, V. Maniezzo and A. Colorni, Ant System: Optimization by a colony of cooperating agents, IEEE Transactions
on Systems, Man, and Cybernetics-Part B, 26(1), 29-41, 1996. IJ.10-SMC96.pdf
Ant-Q
L.M. Gambardella and M. Dorigo, Ant-Q: A Reinforcement Learning Approach to the Traveling Salesman Problem.
Proceedings of ML-95, Twelfth International Conference on Machine Learning, Tahoe City, CA, A. Prieditis and S. Russell (Eds.),
Morgan Kaufmann, 252-260,1995. IC.15-MLC95.ps.gz
Ant Colony System
M. Dorigo & L.M. Gambardella, Ant Colony System: A Cooperative Learning Approach to the Traveling Salesman Problem.
IEEE Transactions on Evolutionary Computation, 1(1):53-66,1997.
IJ.16-TEC97.A4.pdf
Max-Min Ant System
T. Stützle and H. H. Hoos, MAX-MIN Ant System. Future Generation Computer Systems. 16(8):889--914,2000. FGCS.ps.gz
Rank-based Ant System
B. Bullnheimer, R. F. Hartl and C. Strauss, A New Rank Based Version of the Ant System: A Computational Study.
Central European Journal for Operations Research and Economics, 7(1):25-38, 1999. pom-wp-3-97.ps
ANTS
V. Maniezzo, Exact and approximate nondeterministic tree-search procedures for the quadratic assignment problem,
INFORMS Journal on Computing, 11(4), 358-369, 1999. antqap.ps
Hyper Cube - ACO
C. Blum, A. Roli, and M. Dorigo. HC-ACO: The hyper-cube framework for Ant Colony Optimization.
In Proceedings of the Fourth Metaheuristics International Conference, volume 2, pages 399-403, 2001.
Later, a strongly extended version of this paper has been published in IEEE Transactions on Systems, Man, and Cybernetics -- Part B, 34(2):1161-1172, 2004.
B. Doerr, F. Neumann, D. Sudholt and C. Witt.
On the Runtime Analysis of the 1-ANT ACO Algorithm.
To appear in Proc. of GECCO 2007. Preliminary Version under the title
"On the Influence of Pheromone Updates in ACO Algorithms", Technical Report, Reihe CI, No. CI-223/07,
SFB 531, Universität Dortmund, Germany, 2007.
W.J. Gutjahr. First steps to the runtime complexity analysis of
ant colony optimization, Computers and Operations Research, (to appear), 2007.
Preliminary Version.
F. Neumann, D. Sudholt and C. Witt.
Comparing Variants of MMAS ACO Algorithms on Pseudo-Boolean Functions.
To appear in Proc. of SLS 2007. Preliminary Version: Technical Report, Reihe CI, No. CI-230/07, SFB 531,
Universität Dortmund, Germany, 2007.
W.J. Gutjahr. Mathematical Runtime Analysis of ACO Algorithms: Survey on an Emerging Issue. Swarm Intelligence, 1(1), 2007. In press.
C. Blum and M. Dorigo. Search Bias in Ant Colony Optimization: On the Role of Competition-Balanced Systems. IEEE Transactions on Evolutionary Computation, 9(2):159-174, 2005.
Chapter 4 of [M. Dorigo and T. Stützle, Ant Colony Optimization, MIT Press, 2004].
D. Merkle and M. Middendorf. Modelling the Dynamics of Ant Colony Optimization Algorithms. Evolutionary Computation, 10(3): 235-262, 2002.
W.J. Gutjahr. ACO algorithms with guaranteed convergence to the optimal solution. Information Processing Letters, 82:145-153, 2002. ants3.pdf
T. Stützle and M. Dorigo. A Short Convergence Proof for a Class of ACO Algorithms, IEEE Transactions on Evolutionary Computation, 6(4):358-365, 2002.
W.J. Gutjahr. A graph-based Ant System and its convergence, Future Generation Computer Systems, 16:873-888, 2000. ants5.pdf
The number of applications of ACO algorithms has increased very
strongly over the recent years and ACO has been applied in the
meantime to certainly more than one hundred different problems. For
an overview of ACO applications, we refer to the above mentioned
overview articles.
M. Dorigo, V. Maniezzo and A. Colorni, Positive Feedback as a Search Strategy.
Technical Report No. 91-016, Politecnico di Milano, Italy, 1991. Later published as Optimization by a colony of cooperating agents, IEEE Transactions on Systems, Man, and Cybernetics-Part B, 26(1):29-41,1996. TR.01-ANTS-91-016.ps.gz, IJ.10-SMC96.pdf
A. Colorni, M. Dorigo and V. Maniezzo, Distributed Optimization by Ant Colonies, Proceedings of the First European Conference on Artificial Life, F.J. Varela and P. Bourgine (Eds.), MIT Press, Cambridge, MA, 134-142, 1992. IC.06-ECAL92.ps.gz
A. Colorni and M. Dorigo and V. Maniezzo, An Investigation of Some Properties of an Ant Algorithm, Proceedings of PPSN-II, Second International Conference on Parallel Problem Solving from Nature, R. Manner and B. Manderick (Eds.), Elsevier, Amsterdam, The Netherlands, 509-520, 1992. IC.08-PPSN92.ps.gz
M. Dorigo, Optimization, Learning and Natural Algorithms. Ph.D.Thesis, Politecnico di Milano, Italy, [in Italian], 1992.
L.M. Gambardella and M. Dorigo, Ant-Q: A Reinforcement
Learning Approach to the Traveling Salesman Problem. Proceedings of ML-95, Twelfth International Conference on Machine Learning,
Tahoe City, CA, A. Prieditis and S. Russell (Eds.), Morgan Kaufmann, 252-260,1995. IC.15-MLC95.ps.gz
M. Dorigo & L.M. Gambardella, Ant Colony System:
A Cooperative Learning Approach to the Traveling Salesman Problem, Technical Report TR/IRIDIA/1996-5, IRIDIA, Université
Libre de Bruxelles, 1996. Later published in IEEE Transactions on Evolutionary Computation, 1(1):53-66,1997. IJ.16-TEC97.A4.pdf
T. Stützle and H. H. Hoos, Improving the Ant System:
A detailed report on the MAX-MIN Ant System. Technical report AIDA-96-12, FG Intellektik, FB Informatik,
TU Darmstadt, 1996. TR.AIDA-96-12.ps.gz Later published in part as The Max-Min Ant System and Local Search for the Travelling Salesman Problem, IEEE International Conference on Evolutionary Computation, Piscataway, T. Bäck, Z. Michalewicz and X. Yao (Eds.), IEEE Press, pp. 309-314, 1997. ICEC97.ps.gz
R. Schoonderwoerd, O. Holland, J. Bruten and L. Rothkrantz,
Ant-based load balancing in telecommunication networks. Adaptive Behaviour, 5(2), 169-207, 1997.
G. Di Caro and M. Dorigo, AntNet: A mobile agents approach to adaptive routing,
Technical report IRIDIA/97-12, IRIDIA, Université Libre de Bruxelles, 1997. Later published as AntNet: Distributed Strigmergic Control for Communication Networks. Journal of Artificial Intelligence Research (JAIR), 9, 317-365, 1998. TR.07.AntNet-TecRep-97-12.pdf
B. Bullnheimer, R. F. Hartl and C. Strauss,
A New Rank Based Version of the Ant System: A Computational Study, Technical report, Institute of Management Science,
University of Vienna, Austria, 1997. Later published in Central European Journal for Operations Research and Economics,
7(1):25-38, 1999. pom-wp-3-97.ps
V. Maniezzo, Exact and approximate nondeterministic tree-search
procedures for the quadratic assignment problem, INFORMS Journal on Computing, 11(4), 358-369, 1999. antqap.ps
M. Dorigo , G. Di Caro and T. Stützle, special issue on
"Ant Algorithms", Future Generation Computer Systems, Vol. 16, No. 8, June 2000.
O. Cordon, F. Herrera and T. Stützle, special issue on "Ant Colony Optimization",
Vol. IX, No.2-3, Mathware and Soft Computing, November, 2002.
M.Dorigo, L.M. Gambardella, M. Middendorf and T. Stützle,
special section on "Ant Colony Optimization", Vol. 6, No. 4, IEEE Transactions on Evolutionary Computation, July 2002.
M. Dorigo, L. M. Gambardella, M. Birattari, A. Martinoli, R. Poli, and T. Stützle. Ant Colony Optimization and Swarm Intelligence: 5th International Workshop, ANTS 2006. LNCS 4150. Springer Verlag, Berlin, Germany, 2006.
M. Dorigo, M. Birattari, C. Blum, L. M. Gambardella, F. Mondada, and T. Stützle. Ant Colony Optimization and Swarm Intelligence: 4th International Workshop, ANTS 2004. LNCS 3172. Springer Verlag, Berlin, Germany, 2004.
M. Dorigo, G. Di Caro, M. Sampels. Ant Algorithms: 3rd International Workshop, ANTS 2002. LNCS 2463. Springer Verlag, Berlin, Germany, 2002.
M. Dorigo, M. Middendorf and T. Stützle. ANTS' 2000, From Ant Colonies
to Artificial Ants: Second International Workshop on Ant Algorithms, Brussels, Belgium, September, 2000.
M. Dorigo. ANTS' 98, From Ant Colonies
to Artificial Ants: First International Workshop on Ant Colony Optimization, ANTS 98, Brussels, Belgium, October, 1998.
