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

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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).

Keywords:optimization, evolutionary computation, swarm intelligence, local search, continuous optimization, combinatorial optimization, inductive programming, supervised machine learning
Work type:Article (dk_c)
Typology:1.01 - Original Scientific Article
Organization:EF - School of Economics and Business
Publication status in journal:Published
Article version:Publisher's version of article
Number of pages:34 str.
Numbering:Vol. 11, iss. 11, art. 4774
ISSN on article:2076-3417
DOI:10.3390/app11114774 This link opens in a new window
COBISS.SI-ID:64772611 This link opens in a new window
Publication date in RUL:09.06.2021
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Record is a part of a journal

Title:Applied sciences
Shortened title:Appl. sci.
COBISS.SI-ID:522979353 This link opens in a new window


License:CC BY 4.0, Creative Commons Attribution 4.0 International
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
Licensing start date:23.05.2021

Document is financed by a project

Funder:FCT - Fundação para a Ciência e a Tecnologia, I.P.

Funder:FCT - Fundação para a Ciência e a Tecnologia, I.P.

Funder:FCT - Fundação para a Ciência e a Tecnologia, I.P.

Funder:ARRS - Agencija za raziskovalno dejavnost Republike Slovenije (ARRS)
Funding Programme:Raziskovalni program
Name:Digitalizacija kot gonilo trajnostnega razvoja posameznika, organizacij in družbe

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