An ant colony algorithm aimed at dynamic continuous optimization

Applied Mathematics and Computation

Volumn 181, Issue 1, 2006, Pages 457-467

  Dreo J ^a   Siarry, P ^a  

^a UNIVERSITÉ PARIS EST CRÉTEIL   (France)

Author keywords

[No Author keywords available]

Indexed keywords

ANT COLONY OPTIMIZATION (ACO) ALGORITHMS; DYNAMIC PROBLEMS; NELDER-MEAD ALGORITHM;

ARTIFICIAL INTELLIGENCE; BENCHMARKING; DYNAMIC PROGRAMMING; OPTIMIZATION; PROBLEM SOLVING; TELECOMMUNICATION NETWORKS;

ALGORITHMS;

EID: 33749534855     PISSN: 00963003     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.amc.2005.12.051     Document Type: Article

References (17)

1. A. Berro, Optimisation multiobjectif et stratégie d'évolution en environnement dynamique, PhD thesis, Université Paul Sabatier, Toulouse, 2001.
2. Bonabeau E., Dorigo M., and Theraulaz G. Swarm Intelligence, From Natural to Artificial Systems (1999), Oxford University Press
3. Branke J. Evolutionary Optimization in Dynamic Environments. Genetic Algorithms and Evolutionary Computation vol. 3 (2001), Kluwer Academic Publishers
4. A. Carlisle, Tracking changing extrema with adaptive particle swarm optimizer, in: ISSCI 2002, World Automation Congress, Orlando, USA, 2002.
5. H. Cobb, J. Grefenstette, Genetic algorithms for tracking changing environments, in: Fifth International Conference on Genetic Algorithms, 1993.
6. Di Caro G., and Dorigo M. Ant colonies for adaptive routing in packet-switched communications networks. In: Eiben A., Bäck T., Schoenauer M., and Schwefel H.-P. (Eds). Proceedings of PPSN-V, Fifth International Conference on Parallel Problem Solving from Nature. Lecture Notes in Computer Science vol. 1498 (1998), Springer-Verlag, Berlin, Germany 673-682
7. Di Caro G., and Dorigo M. AntNet: Distributed stigmergic control for communications networks. Journal of Artificial Intelligence Research 9 (1998) 317-365
8. J. Dréo, P. Siarry, Un algorithme de colonie de fourmis en variables continues hybridé avec un algorithme de recherche locale, in: 5ème Congrès de la Société Française de Recherche Opérationnelle et d'Aide à la Décision (ROADEF 2003), Avignon, France, 2003.
9. Dréo J., and Siarry P. Continuous interacting ant colony algorithm based on dense heterarchy. Future Generation Computer Systems 20 5 (2004) 841-856
10. R. Morrison, K. De Jong, A test problem generator for non-stationary environments, in: Congress on Evolutionary Computing, 1999.
11. Nelder J.A., and Mead R. A simplex method for function minimization. Computer Journal 7 (1965) 308-313
12. Ourique C., Biscaia E.J., and Pinto J. The use of particle swarm optimization for dynamical analysis in chemical processes. Computers & Chemical Engineering 26 12 (2002) 1783-1793
13. Schoonderwoerd R., Holland O., Brutent J., and Rothkrantz L. Ant-based load balancing in telecommunication networks. Adaptive Behavior 5 2 (1996) 169-207
14. Taillard E.D., Gambardella L.M., Gendreau M., and Potvin J.-Y. Adaptive memory programming: a unified view of meta-heuristics. European Journal of Operational Research 135 1 (1998) 1-16
15. Xiong Q., and Jutan A. Continuous optimization using a dynamic simplex method. Chemical Engineering Science 58 16 (2003) 3817-3828
16. Yip W., and Marlin T. Designing plant experiments for real-time optimization systems. Control Engineering Practice 11 8 (2003) 837-845
17. Yip W., and Marlin T. The effect of model fidelity on real-time optimization performance. Computers & Chemical Engineering 28 1-2 (2003) 267-280