The GLOBAL Optimization Algorithm

Newly Updated with Java Implementation and Parallelization

By: BalÃ¡zs BÃ¡nhelyi, Tibor Csendes, BalÃ¡zs LÃ©vai

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Paperback | 19 December 2018

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Paperback
124 Pages

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23.5 x 15.49 x 0.66

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This book explores the updated version of the GLOBAL algorithm which contains improvements for a local search algorithm and new Java implementations. Efficiency comparisons to earlier versions and on the increased speed achieved by the parallelization, are detailed. Examples are provided for students as well as researchers and practitioners in optimization, operations research, and mathematics to compose their own scripts with ease. A GLOBAL manual is presented in the appendix to assist new users with modules and test functions.

GLOBAL is a successful stochastic multistart global optimization algorithm that has passed several computational tests, and is efficient and reliable for small to medium dimensional global optimization problems. The algorithm uses clustering to ensure efficiency and is modular in regard to the two local search methods it starts with, but though it can easily apply other local techniques. The strength of this algorithm lays lies in its reliability and adaptive algorithm parameters. The GLOBAL algorithm is free to download in the earlier Fortran, C, and MATLAB implementations.

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