Reasons of ACO's success in TSP

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3172 LNCS, Issue , 2004, Pages 226-237

  Gómez, Osvaldo ^a   Barán, Benjamín ^a  

^a UNIVERSIDAD NACIONAL DE ASUNCIÓN   (Paraguay)

Author keywords

[No Author keywords available]

Indexed keywords

COMBINATORIAL OPTIMIZATION; SWARM INTELLIGENCE; TRAVELING SALESMAN PROBLEM; ARTIFICIAL INTELLIGENCE; OPTIMIZATION;

ANALYTICAL TOOL; ANT COLONIES; ANT COLONY OPTIMIZATION (ACO); COMBINATORIAL OPTIMIZATION PROBLEMS; CONVEX STRUCTURE; FORAGING BEHAVIORS; METAHEURISTIC; SOLUTION SPACE;

ANT COLONY OPTIMIZATION;

EID: 53149136957     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-28646-2_20     Document Type: Conference Paper

References (12)

1. M. Birattari, G. Di Caro, and M. Dorigo. For a Formal Foundation of the Ant Programming Approach to Combinatorial Optimization. Part 1: The problem, the representation, and the general solution strategy. Technical Report TR-H-301, ATR-Human Information Processing Labs, Kyoto, Japan, 2000.
2. K. D. Boese. Cost Versus Distance in the Traveling Salesman Problem. Technical Report 950018, Univ. of California, Los Angeles, Computer Science, May 19, 1995.
3. M. Dorigo and G. Di Caro. The Ant Colony Optimization Meta-Heuristic. In D. Corne, M. Dorigo, and F. Glover, editors, New Ideas in Optimization, pages 11-32. McGraw-Hill, London, 1999.
4. M. Dorigo and T. Stützle. An Experimental Study of the Simple Ant Colony Optimization Algorithm. In 2001 WSES International Conference on Evolutionary Computation (EC'01). WSES-Press International, 2001.
5. M. Guntsch and M. Middendorf. A Population Based Approach for ACO. In S. Cagnoni, J. Gottlieb, E. Hart, M. Middendorf, and G. Raidl, editors, Applications of Evolutionary Computing, Proceedings of EvoWorkshops2002: EvoCOP, EvoIASP, EvoSTim, volume 2279, pages 71-80, Kinsale, Ireland, 3-4 2002. Springer-Verlag.
6. M. Guntsch and M. Middendorf. Applying Population Based ACO to Dynamic Optimization Problems. In Ant Algorithms, Proceedings of Third International Workshop ANTS 2002, volume 2463 of LNCS, pages 111-122, 2002.
7. W. J. Gutjahr. A graph-based Ant System and its convergence. Future Generation Computer Systems, 16(8):873-888, June 2000.
8. W. J. Gutjahr. ACO Algorithms with Guaranteed Convergence to the Optimal Solution. Information Processing Letters, 82(3):145-153, May 2002.
9. T. C. Hu, V. Klee, and D. Larman. Optimization of globally convex functions. SIAM Journal on Control and Optimization, 27(5):1026-1047, Sept. 1989.
10. N. Meuleau and M. Dorigo. Ant colony optimization and stochastic gradient descent. Artificial Life, 8(2):103-121, 2002.
11. T. Stützle and M. Dorigo. A Short Convergence Proof for a Class of Ant Colony Optimization Algorithms. IEEE Transactions on Evolutionary Computation, 6:358-365, Aug. 2002.
12. T. Stützle and H. H. Hoos. MAX-MIN Ant System. Future Generation Computer Systems, 16(8):889-914, June 2000.