Randomized search algorithms for hard combinatorial problems exhibit a large variability of performances. We study the different types of rare events which occur in such out-of-equilibrium stochastic processes and we show how they cooperate in determining the final distribution of running times. As a by-product of our analysis we show how search algorithms are optimized by random restarts.
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Montanari et al. (2002) studied this question.
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