STP: A Stochastic Tunneling Algorithm for Global Optimization

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A stochastic approach to solving continuous function global optimization problems is presented. It builds on the tunneling approach to deterministic optimization presented by Barhen et al, by combining a series of local descents with stochastic searches. The method uses a rejection-based stochastic procedure to locate new local minima descent regions and a fixed Lipschitz-like constant to reject unpromising regions in the search space, thereby increasing the efficiency of the tunneling process. The algorithm is easily implemented in low-dimensional problems and scales easily to large problems. It is less effective without further heuristics in these latter cases, however. Several improvements to ... continued below

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32 pages

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Oblow, E.M. May 20, 1999.

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Description

A stochastic approach to solving continuous function global optimization problems is presented. It builds on the tunneling approach to deterministic optimization presented by Barhen et al, by combining a series of local descents with stochastic searches. The method uses a rejection-based stochastic procedure to locate new local minima descent regions and a fixed Lipschitz-like constant to reject unpromising regions in the search space, thereby increasing the efficiency of the tunneling process. The algorithm is easily implemented in low-dimensional problems and scales easily to large problems. It is less effective without further heuristics in these latter cases, however. Several improvements to the basic algorithm which make use of approximate estimates of the algorithms parameters for implementation in high-dimensional problems are also discussed. Benchmark results are presented, which show that the algorithm is competitive with the best previously reported global optimization techniques. A successful application of the approach to a large-scale seismology problem of substantial computational complexity using a low-dimensional approximation scheme is also reported.

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32 pages

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  • Other Information: PBD: 20 May 1999

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  • Report No.: ORNL/TM-13737
  • Grant Number: AC05-00OR22725
  • DOI: 10.2172/814395 | External Link
  • Office of Scientific & Technical Information Report Number: 814395
  • Archival Resource Key: ark:/67531/metadc736924

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Office of Scientific & Technical Information Technical Reports

Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

Office of Scientific and Technical Information (OSTI) is the Department of Energy (DOE) office that collects, preserves, and disseminates DOE-sponsored research and development (R&D) results that are the outcomes of R&D projects or other funded activities at DOE labs and facilities nationwide and grantees at universities and other institutions.

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Creation Date

  • May 20, 1999

Added to The UNT Digital Library

  • Oct. 18, 2015, 6:40 p.m.

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  • Jan. 3, 2017, 1:28 p.m.

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Oblow, E.M. STP: A Stochastic Tunneling Algorithm for Global Optimization, report, May 20, 1999; United States. (digital.library.unt.edu/ark:/67531/metadc736924/: accessed October 19, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.