Investigating the enhanced Best Performance Algorithm for Annual Crop Planning problem based on economic factors

The Annual Crop Planning (ACP) problem was a recently introduced problem in the literature. This study further expounds on this problem by presenting a new mathematical formulation, which is based on market economic factors. To determine solutions, a new local search metaheuristic algorithm is inves...

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Detalles Bibliográficos
Autores principales: Adewumi, Aderemi Oluyinka, Chetty, Sivashan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5549700/
https://www.ncbi.nlm.nih.gov/pubmed/28792495
http://dx.doi.org/10.1371/journal.pone.0180813
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author Adewumi, Aderemi Oluyinka
Chetty, Sivashan
author_facet Adewumi, Aderemi Oluyinka
Chetty, Sivashan
author_sort Adewumi, Aderemi Oluyinka
collection PubMed
description The Annual Crop Planning (ACP) problem was a recently introduced problem in the literature. This study further expounds on this problem by presenting a new mathematical formulation, which is based on market economic factors. To determine solutions, a new local search metaheuristic algorithm is investigated which is called the enhanced Best Performance Algorithm (eBPA). eBPA’s results are compared against two well-known local search metaheuristic algorithms; these include Tabu Search and Simulated Annealing. The results show the potential of the eBPA for continuous optimization problems.
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spelling pubmed-55497002017-08-12 Investigating the enhanced Best Performance Algorithm for Annual Crop Planning problem based on economic factors Adewumi, Aderemi Oluyinka Chetty, Sivashan PLoS One Research Article The Annual Crop Planning (ACP) problem was a recently introduced problem in the literature. This study further expounds on this problem by presenting a new mathematical formulation, which is based on market economic factors. To determine solutions, a new local search metaheuristic algorithm is investigated which is called the enhanced Best Performance Algorithm (eBPA). eBPA’s results are compared against two well-known local search metaheuristic algorithms; these include Tabu Search and Simulated Annealing. The results show the potential of the eBPA for continuous optimization problems. Public Library of Science 2017-08-08 /pmc/articles/PMC5549700/ /pubmed/28792495 http://dx.doi.org/10.1371/journal.pone.0180813 Text en © 2017 Adewumi, Chetty http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Adewumi, Aderemi Oluyinka
Chetty, Sivashan
Investigating the enhanced Best Performance Algorithm for Annual Crop Planning problem based on economic factors
title Investigating the enhanced Best Performance Algorithm for Annual Crop Planning problem based on economic factors
title_full Investigating the enhanced Best Performance Algorithm for Annual Crop Planning problem based on economic factors
title_fullStr Investigating the enhanced Best Performance Algorithm for Annual Crop Planning problem based on economic factors
title_full_unstemmed Investigating the enhanced Best Performance Algorithm for Annual Crop Planning problem based on economic factors
title_short Investigating the enhanced Best Performance Algorithm for Annual Crop Planning problem based on economic factors
title_sort investigating the enhanced best performance algorithm for annual crop planning problem based on economic factors
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5549700/
https://www.ncbi.nlm.nih.gov/pubmed/28792495
http://dx.doi.org/10.1371/journal.pone.0180813
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