Backbones in optimization and approximation

IJCAI International Joint Conference on Artificial Intelligence

Volumn , Issue , 2001, Pages 254-259

  Slaney, John ^a   Walsh, Toby ^b  

^a AUSTRALIAN NATIONAL UNIVERSITY   (Australia)

^b UNIVERSITY OF YORK   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATE SOLUTION; APPROXIMATION PROBLEMS; DECISION PROBLEMS; GRAPH COLORINGS; NUMBER PARTITIONING; OPTIMIZATION PROBLEMS; PROBLEM HARDNESS; TRAVELING SALESPERSON PROBLEM;

ARTIFICIAL INTELLIGENCE; HARDNESS;

OPTIMIZATION;

EID: 84880914510     PISSN: 10450823     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (19)

1. D. Achlioptas, C. Gomes, H. Kautz, and B. Selman. Generating satisfiable problem instances. In Proc. of 17th Nat. Conf. on AI. 2000.
2. K.D. Boese. Cost versus distance in the traveling salesman problem. Technical Report CSD-950018, UCLA Computer Science Department, 1995.
3. B. Bollobas, C. Borgs, J. Chayes, J.H. Kim, and D.B. Wilson. The scaling window of the 2-SAT transition. Random Structures and Algorithms, 2001. To appear. Available from dimacs.rutgers.edu/~dbwilson/2sat/.
4. D. Brelaz. New methods to color the vertices of a graph. Communications of ACM, 22:251-256, 1979. (Pubitemid 9452014)
5. P. Cheeseman, B. Kanefsky, and W.M. Taylor. Where the really hard problems are. In Proc. of the 12th IJCAI, pages 331-337. 1991.
6. J. Culberson and I.P. Gent. Frozen development in graph coloring. Theoretical Computer Science, 2001. To appear. Available from www.apes.cs.strath.ac.uk/apesreports.html.
7. I.P. Gent and T. Walsh. Analysis of heuristics for number partitioning. Computational Intelligence, 14(3):430-451, 1998. (Pubitemid 128609775)
8. C. Gomes, B. Selman, K. McAloon, and C. Tretkoff. Randomization in backtrack search: Exploiting heavy-tailed profiles for solving hard scheduling problems. In The 4th Int. Conf. on Artificial Intelligence Planning Systems (AIPS'98), 1998.
9. A. Kamath, R. Motwani, K. Palem, and P. Spirakis. Tail bounds for occupancy and the satisfiability threshold conjecture. Randomized Structure and Algorithms, 7:59-80, 1995.
10. S. Kirkpatrick and G. Toulouse. Configuration space analysis of the traveling salesman problem. J. de Physique, 46:1277-1292, 1985.
11. R. Korf. From approximate to optimal solutions: A case study of number partitioning. In Proc. of the 14th IJCAI. 1995.
12. D. Mitchell, B. Selman, and H. Levesque. Hard and Easy Distributions of SAT Problems. In Proc. of the 10th Nat. Conf. on AI, pages 459-465. 1992.
13. R. Monasson, R. Zecchina, S. Kirkpatrick, B. Selman, and L. Troyansky. Determining computational complexity for characteristic 'phase transitions'. Nature, 400:133-137, 1998.
14. A. Parkes. Clustering at the phase transition. In Proc. of the 14th Nat. Conf. on AI, pages 340-345. 1997.
15. J. Schneider, C. Froschhammer, I. Morgernstern, T. Husslein, and J.M. Singer. Searching for backbones - an efficient parallel algorithm for the traveling salesman problem. Comput. Phys. Commun., 96:173-188, 1996. (Pubitemid 126387740)
16. J. Singer, I.P. Gent, and A. Smaill. Backbone fragility and the local search cost peak. Journal of Artificial Intelligence Research, 12:235-270, 2000.
17. J. Singer, I.P. Gent, and A. Smaill. Local search on random 2+p-SAT. In Proc. of the 14th ECAI. 2000.
18. J. Slaney and S. Thiébaux. Linear time near-optimal planning in the blocks world. In Proc. of 13th Nat. Conf. on AI, pages 1208-1214. 1996.
19. J. Slaney and S. Thiébaux. On the hardness of decision and optimisation problems. In Proc. of the 13th ECAI, pages 244-248. 1998.