Towards the development of self-ant systems

Genetic and Evolutionary Computation Conference, GECCO'11

Volumn , Issue , 2011, Pages 1947-1954

  Tavares, Jorge ^a   Pereira, Francisco B ^a  

^a UNIVERSITY OF COIMBRA   (Portugal)

Author keywords

Pheromone update methods; Self ant systems; Self generation

Indexed keywords

ANT COLONY ALGORITHMS; ANT COLONY OPTIMIZATION ALGORITHMS; COMPUTATIONAL FRAMEWORK; OPTIMIZATION PROBLEMS; PHEROMONE STRATEGY; PHEROMONE UPDATE METHODS; QUADRATIC ASSIGNMENT PROBLEMS; SELF-ANT SYSTEMS; SELF-GENERATION; STRONGLY-TYPED GENETIC PROGRAMMING;

EVOLUTIONARY ALGORITHMS; OPTIMIZATION;

GENETIC PROGRAMMING;

EID: 84860410761     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2001576.2001838     Document Type: Conference Paper

References (17)

1. Dorigo, M., Stützle, T.: Ant Colony Optimization. MIT Press (2004)
2. Botee, H.M., Bonabeau, E.: Evolving ant colony optimization. Adv. Complex Systems 1 (1998) 149-159
3. Poli, R., Langdon, W.B., McPhee, N.F.: A field guide to genetic programming. Published via http://lulu.com and freely available at http://www.gp-field-guide.org.uk (2008) (With contributions by J. R. Koza).
4. Tavares, J., Pereira, F.B.: Designing pheromone update strategies with strongly typed genetic programming. In: EuroGP 2011 Proceedings. Lecture Notes in Computer Science, Springer (2010)
5. Stutzle, T., Hoos, H.: Maxmin ant system and local search for the traveling salesman problem. In: ICEC Proceedings, IEEE Press (1997) 309-314
6. Montana, D.J.: Strongly typed genetic programming. Evolutionary Computation Journal 3 (1995) 199-230
7. Tavares, J., Pereira, F.B.: Evolving strategies for updating pheromone trails: A case study with the tsp. In: PPSN XI Proceedings. Volume 6239 of Lecture Notes in Computer Science., Springer (2010) 523-532
8. Ross, P.: Hyper-heuristics. In Burke, E., Kendall, G., eds.: Search Methodologies. Springer (2005) 529-556
9. Burke, E.K., Hyde, M., Kendall, G., Ochoa, G., Ozcan, E., Qu, R.: Hyper-heuristics: A survey of the state of the art. Technical Report NOTTCS TR SUB 0906241418-2747, University of Nottingham (2010)
10. Krasnogor, N., Blackburnem, B., Hirst, J., Burke, E.: Multimeme algorithms for protein structure prediction. In: PPSN VII Proceedings. Volume 2439 of LNCS., Springer (2002) 769-778
11. Burke, E.K., Hyde, M.R., Kendall, G., Ochoa, G., Ozcan, E., Woodward, J.R.: Exploring hyper-heuristic methodologies with genetic programming. In: Computational Intelligence: Collaboration, Fusion and Emergence. Springer (2009) 177-201
12. Diosan, L., Oltean, M.: Evolutionary design of evolutionary algorithms. Genetic Programming and Evolvable Machines 10 (2009) 263-306
13. White, T., Pagurek, B., Oppacher, F.: ASGA: Improving the ant system by integration with genetic algorithms. In: Proceedings of the 3rd Genetic Programming Conference, MK (1998) 610-617
14. Poli, R., Langdon, W.B., Holland, O.: Extending particle swarm optimisation via genetic programming. In: EuroGP 2005 Proceedings. (2005) 291-300 (Pubitemid 41274034)
15. Diosan, L., Oltean, M.: Evolving the structure of the particle swarm optimization algorithms. In: EvoCOP 2006 Proceedings. (2006) 25-36 (Pubitemid 44019271)
16. Runka, A.: Evolving an edge selection formula for ant colony optimization. In: GECCO 2009 Proceedings. (2009) 1075-1082
17. Stutzle, T.: Max-min ant system for the quadratic assignment problem. Technical Report AIDA-97-4, FB Informatik, TU Darmstadt (1997)