20.500.12556/RUL-127465
General Purpose Optimization Library (GPOL)
a flexible and efficient multi-purpose optimization library in Python
Several interesting libraries for optimization have been proposed. Some focus on individual optimization algorithms, or limited sets of them, and others focus on limited sets of problems. Frequently, the implementation of one of them does not precisely follow the formal definition, and they are difficult to personalize and compare. This makes it difficult to perform comparative studies and propose novel approaches. In this paper, we propose to solve these issues with the General Purpose Optimization Library (GPOL): a flexible and efficient multipurpose optimization library that covers a wide range of stochastic iterative search algorithms, through which flexible and modular implementation can allow for solving many different problem types from the fields of continuous and combinatorial optimization and supervised machine learning problem solving. Moreover, the library supports full-batch and mini-batch learning and allows carrying out computations on a CPU or GPU. The package is distributed under an MIT license. Source code, installation instructions, demos and tutorials are publicly available in our code hosting platform (the reference is provided in the Introduction).
optimization
evolutionary computation
swarm intelligence
local search
continuous
optimization
combinatorial optimization
inductive programming
supervised machine learning
true
false
true
Angleški jezik
Angleški jezik
Članek v reviji
2021-06-09 08:58:00
2021-06-09 09:23:28
2022-09-06 03:51:29
0000-00-00 00:00:00
2021
0
0
34 str.
iss. 11, art. 4774
Vol. 11
2021
0000-00-00
Zaloznikova
Objavljeno
NiDoloceno
0000-00-00
0000-00-00
0000-00-00
004:78
2076-3417
10.3390/app11114774
64772611
RAZ_Bakurov_Illya_2021.pdf
RAZ_Bakurov_Illya_2021.pdf
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406f6178-c8f3-11eb-a523-00155dcfd717
https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=143874
https://www.mdpi.com/2076-3417/11/11/4774
0
450a9d2d-c8f3-11eb-a523-00155dcfd717
https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=143875
Ekonomska fakulteta
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