A New Genetic-Based Tabu Search Algorithm For Unit Commitment Problem

This paper presents a new algorithm based on integrating the use of genetic algorithms and tabu search methods to solve the unit commitment problem. The proposed algorithm, which is mainly based on genetic algorithms incorporates tabu search method to generate new population members in the reproduct...

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Main Author: Mantawy, A. H. (author)
Other Authors: Abdel-Magid, Y. L. (author), Selim, S.Z. (author), unknown (author)
Format: article
Published: 2020
Subjects:
Online Access:https://eprints.kfupm.edu.sa/id/eprint/2545/1/a_new_genetic_based_tabu_search_algorith_mantawy_isi_000078737900001.pdf
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author Mantawy, A. H.
author2 Abdel-Magid, Y. L.
Selim, S.Z.
unknown
author2_role author
author
author
author_facet Mantawy, A. H.
Abdel-Magid, Y. L.
Selim, S.Z.
unknown
author_role author
dc.creator.none.fl_str_mv Mantawy, A. H.
Abdel-Magid, Y. L.
Selim, S.Z.
unknown
dc.date.*.fl_str_mv 2020
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv https://eprints.kfupm.edu.sa/id/eprint/2545/1/a_new_genetic_based_tabu_search_algorith_mantawy_isi_000078737900001.pdf
A New Genetic-Based Tabu Search Algorithm For Unit Commitment Problem. Electric Power Systems Research, 49. pp. 71-78.
dc.language.none.fl_str_mv en
dc.publisher.none.fl_str_mv ELSEVIER SCIENCE SA
dc.relation.none.fl_str_mv https://eprints.kfupm.edu.sa/id/eprint/2545/
dc.rights.*.fl_str_mv info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Computer
dc.title.none.fl_str_mv A New Genetic-Based Tabu Search Algorithm For Unit Commitment Problem
dc.type.none.fl_str_mv Article
PeerReviewed
info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
description This paper presents a new algorithm based on integrating the use of genetic algorithms and tabu search methods to solve the unit commitment problem. The proposed algorithm, which is mainly based on genetic algorithms incorporates tabu search method to generate new population members in the reproduction phase of the genetic algorithm. In the proposed algorithm, genetic algorithm solution is coded as a mix between binary and decimal representation. A fitness function is constructed from the total operating cost of the generating units without penalty terms. In the tabu search part of the algorithm, a simple short term memory procedure is used to counterthe danger of entrapment at a local optimum by preventing cycling of solutions, and the premature convergence of the genetic algorithm. A significant improvement of the proposed algorithm results, over those obtained by either genetic algorithm or tabu search, has been achieved. Numerical examples also showed the superiority of the proposed algorithm compared with two classical methods in the literature.
eu_rights_str_mv openAccess
format article
id KFUPM_35ec4bdfa95e1d841e9c05e795698574
identifier_str_mv A New Genetic-Based Tabu Search Algorithm For Unit Commitment Problem. Electric Power Systems Research, 49. pp. 71-78.
language_invalid_str_mv en
network_acronym_str KFUPM
network_name_str King Fahd University of Petroleum and Minerals
oai_identifier_str oai::2545
publishDate 2020
publisher.none.fl_str_mv ELSEVIER SCIENCE SA
repository.mail.fl_str_mv
repository.name.fl_str_mv
repository_id_str
spelling A New Genetic-Based Tabu Search Algorithm For Unit Commitment ProblemMantawy, A. H.Abdel-Magid, Y. L.Selim, S.Z.unknownComputerThis paper presents a new algorithm based on integrating the use of genetic algorithms and tabu search methods to solve the unit commitment problem. The proposed algorithm, which is mainly based on genetic algorithms incorporates tabu search method to generate new population members in the reproduction phase of the genetic algorithm. In the proposed algorithm, genetic algorithm solution is coded as a mix between binary and decimal representation. A fitness function is constructed from the total operating cost of the generating units without penalty terms. In the tabu search part of the algorithm, a simple short term memory procedure is used to counterthe danger of entrapment at a local optimum by preventing cycling of solutions, and the premature convergence of the genetic algorithm. A significant improvement of the proposed algorithm results, over those obtained by either genetic algorithm or tabu search, has been achieved. Numerical examples also showed the superiority of the proposed algorithm compared with two classical methods in the literature.ELSEVIER SCIENCE SAArticlePeerReviewedinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://eprints.kfupm.edu.sa/id/eprint/2545/1/a_new_genetic_based_tabu_search_algorith_mantawy_isi_000078737900001.pdf A New Genetic-Based Tabu Search Algorithm For Unit Commitment Problem. Electric Power Systems Research, 49. pp. 71-78. enhttps://eprints.kfupm.edu.sa/id/eprint/2545/2020info:eu-repo/semantics/openAccessoai::25452019-11-01T13:44:45Z
spellingShingle A New Genetic-Based Tabu Search Algorithm For Unit Commitment Problem
Mantawy, A. H.
Computer
status_str publishedVersion
title A New Genetic-Based Tabu Search Algorithm For Unit Commitment Problem
title_full A New Genetic-Based Tabu Search Algorithm For Unit Commitment Problem
title_fullStr A New Genetic-Based Tabu Search Algorithm For Unit Commitment Problem
title_full_unstemmed A New Genetic-Based Tabu Search Algorithm For Unit Commitment Problem
title_short A New Genetic-Based Tabu Search Algorithm For Unit Commitment Problem
title_sort A New Genetic-Based Tabu Search Algorithm For Unit Commitment Problem
topic Computer
url https://eprints.kfupm.edu.sa/id/eprint/2545/1/a_new_genetic_based_tabu_search_algorith_mantawy_isi_000078737900001.pdf