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Cited by 12,067

The DOI matches its Crossref record.

Ant system: optimization by a colony of cooperating agents

Dorigo, M., Maniezzo, V., Colorni, A.·1996·IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)
DOI 10.1109/3477.484436
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Abstract

An analogy with the way ant colonies function has suggested the definition of a new computational paradigm, which we call ant system (AS). We propose it as a viable new approach to stochastic combinatorial optimization. The main characteristics of this model are positive feedback, distributed computation, and the use of a constructive greedy heuristic. Positive feedback accounts for rapid discovery of good solutions, distributed computation avoids premature convergence, and the greedy heuristic helps find acceptable solutions in the early stages of the search process. We apply the proposed methodology to the classical traveling salesman problem (TSP), and report simulation results. We also discuss parameter selection and the early setups of the model, and compare it with tabu search and simulated annealing using TSP. To demonstrate the robustness of the approach, we show how the ant system (AS) can be applied to other optimization problems like the asymmetric traveling salesman, the quadratic assignment and the job-shop scheduling. Finally we discuss the salient characteristics-global data structure revision, distributed communication and probabilistic transitions of the AS.

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Metadata

Authors
Dorigo, M., Maniezzo, V., & Colorni, A.
Venue
IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
1996-02
Volume
26
Issue
1
Pages
29-41
ISSN
  • 1083-4419 (ISSN-L)
  • 1941-0492
DOI
10.1109/3477.484436
OpenAlex
W2107941094
Cited by
12,067
References
0
FWCI
48.06
Type
journal article
Language
en
Open access
closed

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