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Dataset "Improving the applicability of genetic algorithms to real problems"

Dataset "Improving the applicability of genetic algorithms to real problems"
Dataset "Improving the applicability of genetic algorithms to real problems"
Dataset for the thesis for the degree of Doctorate of Philosophy, University of Southampton 2021. "Improving the applicability of genetic algorithms to real problems", by Przemyslaw Andrzej Grudniewski. - The Dataset is separated according to chapters of the Thesis - In each chapter the data is separated into 3 main categories: a) Figures in folder "Figures"; b) Table data in folder "Processed Table Data"; and c) raw data files in folder "Raw Data" - Additionally, the code for the algorithm used to conduct all experiments is provided in "Additional_Data_Code_ReadMe.7z"
Genetic Algortihms, Optimisation, Multi-objective optimisation, Multi-level selection, artificial intelligence
University of Southampton
Grudniewski, Przemyslaw Andrzej
30349b11-4667-41d6-9b45-587c46254a2f
Sobey, Adam
e850606f-aa79-4c99-8682-2cfffda3cd28
Grudniewski, Przemyslaw Andrzej
30349b11-4667-41d6-9b45-587c46254a2f
Sobey, Adam
e850606f-aa79-4c99-8682-2cfffda3cd28

Grudniewski, Przemyslaw Andrzej (2021) Dataset "Improving the applicability of genetic algorithms to real problems". University of Southampton doi:10.5258/SOTON/D1709 [Dataset]

Record type: Dataset

Abstract

Dataset for the thesis for the degree of Doctorate of Philosophy, University of Southampton 2021. "Improving the applicability of genetic algorithms to real problems", by Przemyslaw Andrzej Grudniewski. - The Dataset is separated according to chapters of the Thesis - In each chapter the data is separated into 3 main categories: a) Figures in folder "Figures"; b) Table data in folder "Processed Table Data"; and c) raw data files in folder "Raw Data" - Additionally, the code for the algorithm used to conduct all experiments is provided in "Additional_Data_Code_ReadMe.7z"

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More information

Published date: 11 January 2021
Keywords: Genetic Algortihms, Optimisation, Multi-objective optimisation, Multi-level selection, artificial intelligence

Identifiers

Local EPrints ID: 446113
URI: http://eprints.soton.ac.uk/id/eprint/446113
PURE UUID: 400ea174-9d37-4442-8120-ad81e1324798
ORCID for Adam Sobey: ORCID iD orcid.org/0000-0001-6880-8338

Catalogue record

Date deposited: 20 Jan 2021 17:38
Last modified: 18 Feb 2021 17:09

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