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General Purpose Optimization Library (GPOL) : a flexible and efficient multi-purpose optimization library in Python
ID Bakurov, Illya (Avtor), ID Buzzelli, Marco (Avtor), ID Castelli, Mauro (Avtor), ID Vanneschi, Leonardo (Avtor), ID Schettini, Raimondo (Avtor)

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Izvleček
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).

Jezik:Angleški jezik
Ključne besede:optimization, evolutionary computation, swarm intelligence, local search, continuous optimization, combinatorial optimization, inductive programming, supervised machine learning
Vrsta gradiva:Članek v reviji (dk_c)
Tipologija:1.01 - Izvirni znanstveni članek
Organizacija:EF - Ekonomska fakulteta
Leto izida:2021
Status objave pri reviji:Objavljeno
Verzija članka:Založnikova različica članka
Št. strani:34 str.
Številčenje:Vol. 11, iss. 11, art. 4774
UDK:004:78
ISSN pri članku:2076-3417
DOI:10.3390/app11114774 Povezava se odpre v novem oknu
COBISS.SI-ID:64772611 Povezava se odpre v novem oknu
Datum objave v RUL:09.06.2021
Število ogledov:254
Število prenosov:66
Metapodatki:XML RDF-CHPDL DC-XML DC-RDF
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Gradivo je del revije

Naslov:Applied sciences
Skrajšan naslov:Appl. sci.
Založnik:MDPI
ISSN:2076-3417
COBISS.SI-ID:522979353 Povezava se odpre v novem oknu

Licence

Licenca:CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
Povezava:http://creativecommons.org/licenses/by/4.0/deed.sl
Opis:To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.
Začetek licenciranja:23.05.2021

Gradivo je financirano iz projekta

Financer:FCT - Fundação para a Ciência e a Tecnologia, I.P.
Številka projekta:DSAIPA/DS/0022/2018
Akronim:GADgET

Financer:FCT - Fundação para a Ciência e a Tecnologia, I.P.
Številka projekta:PTDC/CCI-INF/29168/2017
Akronim:BINDER

Financer:FCT - Fundação para a Ciência e a Tecnologia, I.P.
Številka projekta:DSAIPA/DS/0113/2019
Akronim:AICE

Financer:ARRS - Agencija za raziskovalno dejavnost Republike Slovenije (ARRS)
Program financ.:Raziskovalni program
Številka projekta:P5-0410
Naslov:Digitalizacija kot gonilo trajnostnega razvoja posameznika, organizacij in družbe

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