The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Ant Colony Optimization and Swarm Intelligence: 4th International Workshop, ANTS 2004, Brussels, Belgium, September 5-8, 2004. Proceedings
Open accessAbstract
This paper presents how the Ant Colony Optimization (ACO) metaheuristic can be extended to continuous search domains and applied to both continuous and mixed discrete-continuous optimization problems. The paper describes the general underlying idea, enumerates some possible design choices, presents a first implementation, and provides some preliminary results obtained on well-known benchmark problems. The proposed method is compared to other ant, as well as non-ant methods for continuous optimization.
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Cites
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 · Cited by 12,067
Ant colony system: a cooperative learning approach to the traveling salesman problem
Dorigo, M., & Gambardella, L. M. (1997) · IEEE Transactions on Evolutionary Computation · doi:10.1109/4235.585892 · Cited by 8,081
The ant system applied to the quadratic assignment problem
Maniezzo, V., & Colorni, A. (1999) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/69.806935 · Cited by 744
A new version of ant system for subset problems
Leguizamon, G., & Michalewicz, Z. (2003) · Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406) · doi:10.1109/cec.1999.782655 · Cited by 215
Ants can solve constraint satisfaction problems
Solnon, C. (2002) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2002.802449 · Cited by 196
Search Bias in Constructive Metaheuristics and Implications for Ant Colony Optimisation
Montgomery, J., Randall, M., & Hendtlass, T. (2004) · Lecture notes in computer science · doi:10.1007/978-3-540-28646-2_39 · Cited by 16
Heuristics for ant colony optimisation using the generalised assignment problem
Randall, M. (2005) · IEEE Congress on Evolutionary Computation (CEC) · doi:10.1109/cec.2004.1331130 · Cited by 16
Cited by
Particle swarm optimization: An overview
Poli, R., Kennedy, J., & Blackwell, T. (2007) · Swarm Intelligence · doi:10.1007/s11721-007-0002-0 · Cited by 21,101
Intelligent Frequency Control in an AC Microgrid: Online PSO-Based Fuzzy Tuning Approach
Bevrani, H., Habibi, F., Babahajyani, P., Watanabe, M., & Mitani, Y. (2012) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2012.2196806 · Cited by 599
Chemical-Reaction-Inspired Metaheuristic for Optimization
Lam, A. Y. S., & Li, V. O. K. (2010) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2009.2033580 · Cited by 587
A Multi-Facet Survey on Memetic Computation
Chen, X., Ong, Y.-S., Lim, M.-H., & Tan, K. C. (2011) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2011.2132725 · Cited by 512
A new bio-inspired optimisation algorithm: Bird Swarm Algorithm
Meng, X.-B., Gao, X. Z., Lu, L., Liu, Y., & Zhang, H. (2016) · Journal of Experimental & Theoretical Artificial Intelligence · doi:10.1080/0952813x.2015.1042530 · Cited by 469
Metadata
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg
- Published
- 2004
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W4292408555
- Cited by
- 1,511
- References
- 7
- FWCI
- 44.67
- Type
- conference paper
- Language
- en
- Open access
- green
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