Modeling the dynamics of ant colony optimization

Evolutionary Computation

Volumn 10, Issue 3, 2002, Pages 235-262

  Merkle, Daniel ^a   Middendorf, Martin ^b  

^a UNIVERSITY OF KARLSRUHE   (Germany)

^b CATHOLIC UNIVERSITY OF EICHSTÄTT INGOLSTADT   (Germany)

Author keywords

ACO algorithms; ACO model; Ant colony optimization; Dynamic behavior; Fixed points

Indexed keywords

PHEROMONE;

ALGORITHM; ANIMAL; ANIMAL BEHAVIOR; ANT; ARTICLE; BIOLOGICAL MODEL; PHYSIOLOGY; POPULATION DYNAMICS;

ALGORITHMS; ANIMALS; ANTS; BEHAVIOR, ANIMAL; MODELS, BIOLOGICAL; PHEROMONES; POPULATION DYNAMICS;

EID: 0036715610     PISSN: 10636560     EISSN: None     Source Type: Journal    
DOI: 10.1162/106365602760234090     Document Type: Article

References (20)

1. Bruce, I. D. and Simpson, R. J. (1999). Evolution Determined by Trajectory of Expected Populations: Sufficient Conditions, with Application to Crossover. Evolutionary Computation, 7(2):151-171.
2. Dorigo, M. (1992). Optimization, Learning and Natural Algorithms (in Italian). Ph.D. thesis, Dipartimento di Elettronica, Politecnico di Milano, Milan, Italy.
3. Dorigo, M. and Di Caro, G. (1999). The ant colony optimization meta-heuristic. In Corne, D., Dorigo, M., and Glover, F., editors, New Ideas in Optimization, pages 11-32, McGraw-Hill, London, UK.
4. Dorigo, M., Maniezzo, V., and Colorni, A. (1996). The Ant System: Optimization by a Colony of Cooperating Agents. IEEE Transactions on Systems, Man, and Cybernetics - Part B, 26:29-41.
5. Gutjahr, W. (2000). A graph-based Ant System and its convergence, Future Generation Computer Systems, 16:873-888.
6. Gutjahr, W. (2002). ACO algorithms with guaranteed convergence to the optimal solution. Information Processing Letters, 82:145-153.
7. Merkle, D. and Middendorf, M. (2000). An Ant Algorithm with a new Pheromone Evaluation Rule for Total Tardiness Problems. In Cagrioni, S. et al., editors, Real-World Applications of Evolutionary Computing, Proceedings of EvoWorkshops 2000, LNCS, 1803:287-296, Springer Verlag, Berlin, Germany.
8. Merkle, D. and Middendorf, M. (2001a). A New Approach to Solve Permutation Scheduling Problems with Ant Colony Optimization. In Boers, E. J. W. et al., editors, Applications of Evolutionary Computing: Proceedings of EvoWorkshops 2001, LNCS, 2037:213-222, Springer Verlag, Berlin, Germany.
9. Merkle, D. and Middendorf, M. (2001b). On the Behaviour of Ant Algorithms: Studies on Simple Problems. In Proceedings of the Fourth Metaheuristics International Conference (MIC'20001), pages 573-577.
10. Merkle, D., Middendorf, M., and Schmeck, H. (2002). Ant Colony Optimization for Resource-Constrained Project Scheduling. IEEE Transactions on Evolutionary Computation, in press.
11. Mitchell, M. and Forrest, S. (1997). Royal Road Functions. In Back, T., Fogel, D., and Michalewicz, Z., editors, Handbook of Evolutionary Computation. Oxford University Press, Oxford, UK.
12. van Nimwegen, E., Crutchfield, J. P., and Mitchell, M. (1999). Statistical dynamics of the royal road genetic algorithm. Theoretical Computer Science, 229:41-102.
13. Papadimitriou, C. H. and Steiglitz, K. (1982). Combinatorial Optimization: Algorithms and Complexity. Prentice-Hall, Englewood Cliffs.
14. Prügel-Bennett, A. and Rogers, A. (2001). Modelling GA Dynamics. In Kallel, L., Naudts, B., and Rogers, A., editors. Theoretical Aspects of Evolutionary Computing, pages 59-86, Springer, Berlin, Germany.
15. Prügel-Bennett, A. and Shapiro, J. L. (1994). An Analysis of Genetic Algorithms Using Statistical Mechanics. Physical Review Letters, 72:1305-1309.
16. Rajendran, C. and Ziegler, H. (2001). Ant-Colony Algorithms for Flowshop Scheduling, European Journal of Operational Research, submitted.
17. Stützle, T. and Dorigo, M. (2000). A short convergence proof for a class of ACO algorithms. Technical Report IRIDIA/2000-35, IRIDIA, Universitè Libre de Bruxelles, Belgium.
18. Teich, T. et al. (2001). A new Ant Colony Algorithm for the Job Shop Scheduling Problem. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2001), page 803, Morgan Kaufmann, San Francisco, California.
19. Vose, M. D. (1999). The Simple Genetic Algorithm: Foundations and Theory. MIT Press, Cambridge, Massachusetts.
20. Vose, M. D. and Liepins, G. E. (1991). Punctuated equilibria in genetic search. Complex Systems, 5:31-44.