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Generator Maintenance Scheduling using Exchange Market Algorithm

The Generator Maintenance Schedule model is formulated mathematically as a highly constrained combinatorial optimization problem and it is obligatory to implement a suitable optimization tool to determine the best feasible maintenance schedule. The maintenance schedule obtained has to meet a number...

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Detalles Bibliográficos
Autores principales: Moyo, Learnmore, Nwulu, Nnamdi I., Ekpenyong, Uduakobong E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7262440/
https://www.ncbi.nlm.nih.gov/pubmed/32489912
http://dx.doi.org/10.1016/j.mex.2020.100932
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author Moyo, Learnmore
Nwulu, Nnamdi I.
Ekpenyong, Uduakobong E.
author_facet Moyo, Learnmore
Nwulu, Nnamdi I.
Ekpenyong, Uduakobong E.
author_sort Moyo, Learnmore
collection PubMed
description The Generator Maintenance Schedule model is formulated mathematically as a highly constrained combinatorial optimization problem and it is obligatory to implement a suitable optimization tool to determine the best feasible maintenance schedule. The maintenance schedule obtained has to meet a number of power system constraints. There is increased research in the development of approximate solution methodologies such as heuristic and meta-heuristic techniques [1]. Unlike mathematical methods, metaheuristics can obtain an optimal solution to a complex problem fast and are not subjected to limitations such as linearity, continuity, differentiability and convexity that are faced by mathematical programs [2]. This work presents the application of Exchange Market Algorithm (EMA) to find an optimal maintenance schedule. The algorithm is customized to achieve the following: • Selecting the initial population within the maintenance window constraint to enable faster convergence. • Adapt the algorithm to give discrete solutions. • Penalty function included for constraint handling.
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spelling pubmed-72624402020-06-01 Generator Maintenance Scheduling using Exchange Market Algorithm Moyo, Learnmore Nwulu, Nnamdi I. Ekpenyong, Uduakobong E. MethodsX Energy The Generator Maintenance Schedule model is formulated mathematically as a highly constrained combinatorial optimization problem and it is obligatory to implement a suitable optimization tool to determine the best feasible maintenance schedule. The maintenance schedule obtained has to meet a number of power system constraints. There is increased research in the development of approximate solution methodologies such as heuristic and meta-heuristic techniques [1]. Unlike mathematical methods, metaheuristics can obtain an optimal solution to a complex problem fast and are not subjected to limitations such as linearity, continuity, differentiability and convexity that are faced by mathematical programs [2]. This work presents the application of Exchange Market Algorithm (EMA) to find an optimal maintenance schedule. The algorithm is customized to achieve the following: • Selecting the initial population within the maintenance window constraint to enable faster convergence. • Adapt the algorithm to give discrete solutions. • Penalty function included for constraint handling. Elsevier 2020-05-23 /pmc/articles/PMC7262440/ /pubmed/32489912 http://dx.doi.org/10.1016/j.mex.2020.100932 Text en © 2020 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Energy
Moyo, Learnmore
Nwulu, Nnamdi I.
Ekpenyong, Uduakobong E.
Generator Maintenance Scheduling using Exchange Market Algorithm
title Generator Maintenance Scheduling using Exchange Market Algorithm
title_full Generator Maintenance Scheduling using Exchange Market Algorithm
title_fullStr Generator Maintenance Scheduling using Exchange Market Algorithm
title_full_unstemmed Generator Maintenance Scheduling using Exchange Market Algorithm
title_short Generator Maintenance Scheduling using Exchange Market Algorithm
title_sort generator maintenance scheduling using exchange market algorithm
topic Energy
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7262440/
https://www.ncbi.nlm.nih.gov/pubmed/32489912
http://dx.doi.org/10.1016/j.mex.2020.100932
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