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2008
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Understanding the role of noise in stochastic local search: Analysis and experiments

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Understanding the role of noise in stochastic local search: Analysis and experiments
Stochastic local search (SLS) algorithms have recently been proven to be among the best approaches to solving computationally hard problems. SLS algorithms typically have a number of parameters, optimized empirically, that characterize and determine their performance. In this article, we focus on the noise parameter. The theoretical foundation of SLS, including an understanding of how to the optimal noise varies with problem di
Ole J. Mengshoel
Added 08 Dec 2010
Updated 08 Dec 2010
Type Journal
Year 2008
Where AI
Authors Ole J. Mengshoel
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