A complete anytime algorithm for number partitioning

Artificial Intelligence

Volumn 106, Issue 2, 1998, Pages 181-203

  Korf, Richard E ^a  

^a University of California   (United States)

Author keywords

Anytime algorithm; NP complete; Number partitioning

Indexed keywords

ALGORITHMS; COMPUTATIONAL COMPLEXITY; HEURISTIC METHODS; POLYNOMIALS; PROBLEM SOLVING; SET THEORY;

COMPLETE KARMARKAR-KARP (CKK) METHOD; NUMBER PARTITIONING;

ARTIFICIAL INTELLIGENCE;

EID: 0032320042     PISSN: 00043702     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0004-3702(98)00086-1     Document Type: Article

References (21)

1. J. Bright, S. Kasif, L. Stiller, Exploiting algebraic structure in parallel state space search, in: Proceedings AAAI-94, Seattle, WA, 1994, pp. 1341-1346.
2. M. Boddy, T. Dean, Solving time-dependent planning problems, in: Proceedings IJCAI-89, Detroit, MI, 1989, pp. 979-984.
3. P. Cheeseman, B. Kanefsky, W.M. Taylor, Where the really hard problems are, in: Proceedings IJCAI-91, Sydney, Australia, 1991, pp. 331-337.
4. M.R. Garey, D.S. Johnson, Computers and Intractability: A Guide to the Theory of NP-Completeness, W.H. Freeman, San Francisco, CA, 1979.
5. I.P. Gent, T. Walsh, The number partition phase transition, Technical Report RR-95-185, Department of Computer Science, University of Strathclyde, Glasgow, Scotland, 1995.
6. I.P. Gent, T. Walsh, From approximate to optimal solutions: constructing pruning and propagation rules, in: Proceedings IJCAI-97, Nagoya, Japan, 1997, pp. 1396-1401.
7. W.D. Harvey, M.L. Ginsberg, Limited discrepancy search, in: Proceedings IJCAI-95, Montreal, Quebec, 1995, pp. 607-613.
8. E. Horowitz, S. Sahni, Computing partitions with applications to the Knapsack problem, J. ACM 21 (2) (1974) 277-292.
9. B. Huberman, T. Hogg, Phase transitions in artificial intelligence systems, Artificial Intelligence 33 (2) (1987) 155-171.
10. D.S. Johnson, C.R. Aragon, L.A. McGeoch, C. Schevon, Optimization by simulated annealing: an experimental evaluation, Part II: Graph coloring and number partitioning, Oper. Res. 39 (3) (1991) 378-406.
11. D.R. Jones, M.A. Beltramo, Solving partitioning problems with genetic algorithms, in: R.K. Belew, L.B. Booker (Eds.), Proceedings 4th International Conference on Genetic Algorithms, Morgan Kaufmann, San Mateo, CA, 1991, pp. 442-449.
12. N. Karmarkar, R.M. Karp, The differencing method of set partitioning. Technical Report UCB/CSD 82/113, Computer Science Division, University of California, Berkeley, CA, 1982.
13. N. Karmarkar, R.M. Karp, G.S. Lueker, A.M. Odlyzko, Probabilistic analysis of optimum partitions, J. Appl. Probab. 23 (1986) 626-645.
14. R.M. Karp, Reducibility among combinatorial problems, in: R.E. Miller, J.W. Thatcher (Eds.), Complexity of Computer Computations, Plenum Press, New York, 1972, pp. 85-103.
15. R.E. Korf, From approximate to optimal solutions: a case study of number partitioning, in: Proceedings IJCAI-95, Montreal, Quebec, 1995, pp. 266-272.
16. R.E. Korf, Improved limited discrepancy search, in: Proceedings AAAI-96, Portland, OR, 1996, pp. 286-291.
17. D. Mitchell, B. Selman, H. Levesque, Hard and easy distributions of SAT problems, in: Proceedings AAAI-92, San Jose, CA, 1992, pp. 459-465.
18. W. Ruml. J.T. Ngo, J. Marks, S. Shieber, Easily searched encodings for number partitioning, J. Optim. Theory Appl. 89 (2) (1996).
19. n/4) algorithm for certain NP-complete problems, SIAM J. Comput. 10 (3) (1981) 456-464.
20. B. Yakir, The differencing algorithm LDM for partitioning: a proof of a conjecture of Karmarkar and Karp, Math. Oper. Res. 21 (1996) 85-99.
21. W. Zhang, R.E. Korf, A study of complexity transitions on the asymmetric traveling salesman problem, Artificial Intelligence 81 (1996) 223-239.