منابع مشابه
Splitting for optimization
The splitting method is a well-known method for rare-event simulation, where sample paths of a Markov process are split into multiple copies during the simulation, so as to make the occurrence of a rare event more frequent. Motivated by the splitting algorithm we introduce a novel global optimization method for continuous optimization that is both very fast and accurate. Numerical experiments d...
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متن کاملSplitting for Multi-objective Optimization
We introduce a new multi-objective optimization (MOO) methodology based the splitting technique for rare-event simulation. The method generalizes the elite set selection of the traditional splitting framework, and uses both local and global sampling to sample in the decision space. In addition, an ε-dominance method is employed to maintain good solutions. The algorithm was compared with state-o...
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Abstract. We present in this paper two different classes of general K-splitting algorithms for solving finite-dimensional convex optimization problems. Under the assumption that the function being minimized has a Lipschitz continuous gradient, we prove that the number of iterations needed by the first class of algorithms to obtain an ε-optimal solution is O(1/ε). The algorithms in the second cl...
متن کاملComposite splitting algorithms for convex optimization
Article history: Received 21 April 2010 Accepted 6 June 2011 Available online xxxx
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ژورنال
عنوان ژورنال: Computers & Operations Research
سال: 2016
ISSN: 0305-0548
DOI: 10.1016/j.cor.2016.04.015