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Development of Hybrid Local Stochastic Optimization Methods

Student: Ekaterina Pocherevina

Supervisor: Mikhail Posypkin

Faculty: HSE Tikhonov Moscow Institute of Electronics and Mathematics (MIEM HSE)

Educational Programme: Control Systems and Data Processing in Engineering (Master)

Final Grade: 9

Year of Graduation: 2019

The paper presents methods of stochastic-local search of function minimum. It covers the following methods: an adaptive algorithm of random search, the best sample method with his gradient variation and a granular radial search. Also in the work was presented a hybrid method, obtained on the basis of the above search methods. These methods are compared with each other using special set of test functions, and the best results for some of this function are demonstrated by the hybrid method. In addition, the method for selecting parameters for this method was developed.

Full text (added May 24, 2019)

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