Relevant bibliographies by topics / Multi-start method

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  1. Journal articles

Academic literature on the topic 'Multi-start method'

Author: Grafiati
Published: 4 June 2021
Last updated: 10 February 2022

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Journal articles on the topic "Multi-start method"

1

Dong, Huachao, Baowei Song, Zuomin Dong, and Peng Wang. "Multi-start Space Reduction (MSSR) surrogate-based global optimization method." Structural and Multidisciplinary Optimization 54, no. 4 (2016): 907–26. http://dx.doi.org/10.1007/s00158-016-1450-1.

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Kostenko, V. A. "Multi-Start Method with Cutting for Solving Problems of Unconditional Optimization." Optical Memory and Neural Networks 29, no. 1 (2020): 30–36. http://dx.doi.org/10.3103/s1060992x20010099.

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3

Shirakawa, Masakazu, and Masao Arakawa. "Multi-objective Evaluation Method for Combined Cycle Power Plant Start-up." IFAC-PapersOnLine 51, no. 28 (2018): 19–24. http://dx.doi.org/10.1016/j.ifacol.2018.11.671.

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Shirakawa, Masakazu, and Masao Arakawa. "Multi-objective evaluation method for combined cycle power plant start-up." IFAC Journal of Systems and Control 13 (September 2020): 100101. http://dx.doi.org/10.1016/j.ifacsc.2020.100101.

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5

Huang, M., C. J. Aine, S. Supek, E. Best, D. Ranken, and E. R. Flynn. "Multi-start downhill simplex method for spatio-temporal source localization in magnetoencephalography." Electroencephalography and Clinical Neurophysiology/Evoked Potentials Section 108, no. 1 (1998): 32–44. http://dx.doi.org/10.1016/s0168-5597(97)00091-9.

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6

Pál, László, Tibor Csendes, Mihály Csaba Markót, and Arnold Neumaier. "Black Box Optimization Benchmarking of the GLOBAL Method." Evolutionary Computation 20, no. 4 (2012): 609–39. http://dx.doi.org/10.1162/evco_a_00089.

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GLOBAL is a multi-start type stochastic method for bound constrained global optimization problems. Its goal is to find the best local minima that are potentially global. For this reason it involves a combination of sampling, clustering, and local search. The role of clustering is to reduce the number of local searches by forming groups of points around the local minimizers from a uniformly sampled domain and to start few local searches in each of those groups. We evaluate the performance of the GLOBAL algorithm on the BBOB 2009 noiseless testbed, containing problems which reflect the typical d
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7

James, Tabitha, and Cesar Rego. "Path Relinking with Multi-Start Tabu Search for the Quadratic Assignment Problem." International Journal of Swarm Intelligence Research 2, no. 2 (2011): 52–70. http://dx.doi.org/10.4018/jsir.2011040104.

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This paper introduces a new path relinking algorithm for the well-known quadratic assignment problem (QAP) in combinatorial optimization. The QAP has attracted considerable attention in research because of its complexity and its applicability to many domains. The algorithm presented in this study employs path relinking as a solution combination method incorporating a multistart tabu search algorithm as an improvement method. The resulting algorithm has interesting similarities and contrasts with particle swarm optimization methods. Computational testing indicates that this algorithm produces r
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8

Xu, Yang, Lei Zhu, Zhiyong Cheng, Jingjing Li, and Jiande Sun. "Multi-Feature Discrete Collaborative Filtering for Fast Cold-Start Recommendation." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 01 (2020): 270–78. http://dx.doi.org/10.1609/aaai.v34i01.5360.

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Hashing is an effective technique to address the large-scale recommendation problem, due to its high computation and storage efficiency on calculating the user preferences on items. However, existing hashing-based recommendation methods still suffer from two important problems: 1) Their recommendation process mainly relies on the user-item interactions and single specific content feature. When the interaction history or the content feature is unavailable (the cold-start problem), their performance will be seriously deteriorated. 2) Existing methods learn the hash codes with relaxed optimizatio
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9

YU Fei, 于飞, 林喆 LIN Zhe, 赵跃进 ZHAO Yuejin, 董立泉 DONG Liquan, and 康晓军 KANG Xiaojun. "A fast motion estimation searching method based onthe multi-start and concurrent algorithm." Optical Technique 40, no. 2 (2014): 140–44. http://dx.doi.org/10.3788/gxjs20144002.0140.

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10

OKUDA, Osamu. "A Mesh Partitioning based on Multi-start Method for Parallel Finite Element Analysis." Proceedings of The Computational Mechanics Conference 2003.16 (2003): 753–54. http://dx.doi.org/10.1299/jsmecmd.2003.16.753.

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