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Boosting combinatorial search through randomization (1998)

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by Carla P. Gomes
Citations:269 - 32 self
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BibTeX

@INPROCEEDINGS{Gomes98boostingcombinatorial,
    author = {Carla P. Gomes},
    title = {Boosting combinatorial search through randomization},
    booktitle = {},
    year = {1998},
    pages = {431--437},
    publisher = {AAAI Press}
}

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Abstract

Unpredictability in the running time of complete search procedures can often be explained by the phenomenon of “heavy-tailed cost distributions”, meaning that at any time during the experiment there is a non-negligible probability of hitting a problem that requires exponentially more time to solve than any that has been encountered before (Gomes et al. 1998a). We present a general method for introducing controlled randomization into complete search algorithms. The “boosted ” search methods provably eliminate heavy-tails to the right of the median. Furthermore, they can take advantage of heavy-tails to the left of the median (that is, a nonnegligible chance of very short runs) to dramatically shorten the solution time. We demonstrate speedups of several orders of magnitude for state-of-the-art complete search procedures running on hard, real-world problems.

Citations

636 A machine program for theorem proving - Davis, Logemann, et al. - 1962
463 Pushing the envelope: Planning, propositional logic, and stochastic search - KAUTZ, SELMAN - 1996
323 Dynamic backtracking - Ginsberg - 1993
256 Stable Non-Gaussian Random Processes: Stochastic Models with Infinite Variance - SAMORODNITSKY, S - 1994
207 Domain-independent extensions to GSAT: solving large structured satis ability problems - Selman, Kautz - 1993
182 Using CSP look-back techniques to solve real-world SAT instances - Bayardo, Schrag - 1997
93 Experimental results on the application of satisfiability algorithms to scheduling problems - Crawford, Baker - 1994
75 Heuristic-biased stochastic sampling - Bresina - 1996
75 Easy Problems are Sometimes Hard - Gent, Walsh - 1994
67 B.: Problem structure in the presence of perturbations - Gomes, Selman - 1997
55 Scheduling a major college basketball conference - Nemhauser, Trick - 1998
43 Sparse constraint graphs and exceptionally hard problems - Smith, Grant - 1995
35 The Pareto-Lévy law and the distribution of income - Mandelbrot - 1960
31 Constraint networks. In: Encyclopedia of Artificial Intelligence, 2nd edn - Dechter - 1992
27 Constraint-based reasoning - Freuder, Mackworth, et al. - 1994
24 Stochastic Procedures for Generating Feasible Schedules - Oddi, Smith - 1997
12 An interior point approach to Boolean vector function synthesis - Kamath, Karmarkar, et al. - 1993
8 Min and Anbulagan - Li - 1997
7 Beyond the Black Box: Constraints as objects - Puget, Leconte - 1995
2 Heavy-Tailed Phenomena in Combinatorial Search - Gomes, Selman, et al. - 1998
2 Combinatorial Aspects of Construction of - Schreuder - 1992
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