Title Methods for generation of random numbers in parallel stochastic algorithms for global optimization /
Another Title Atsitiktinių skaičių generavimo paraleliniuose stochastiniuose algoritmuose bendrajam optimizavimui metodai.
Authors Lančinskas, Algirdas ; Žilinskas, Julius
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Is Part of Jaunųjų mokslininkų darbai. 2010, Nr. 2 (27), P. 118-122.. ISSN 1648-8776
Keywords [eng] Random numbers ; Random number generators ; Algorithm, parallel stochastic ; Optimization, global
Abstract [eng] Perfomance of stochastic algorithms for global optimization crucially depends on generation of random numbers. Random number generation methods may vary on features as independence of the generated random numbers, fit to the required distribution, and speed of generation. This paper reviews the main idea and several algorithms for generation of pseudo random numbers. Evaluation criteria of pseudo random numbers generators are also reviewed. Seven widely used random numbers generators (Linear Congruential Generator, Mersenne Twister, Mother At All, C++, Pascal, Matlab and Fortran) are experimentally compared evaluating the distribution of random numbers, correlation of sequences and speed of generation. In parallel computations correlation of sequences may depend on the seed of pseudo random numbers generators. Therefore several ways for construction of the seeds are compared considering correlation of generated sequences of random numbers when computations are performed in parallel computers.
Type Journal article
Language English
Publication date 2010