Enhancing the Harmony Search Algorithm Performance on Constrained Numerical Optimization
In this paper, an improved harmony search (ImHS) algorithm is presented. HS is a simple but efficient metaheuristic method explored in recent literature, that simulates the process of musical improvisation. Two modifications for parameter tuning are proposed to enhance the algorithm performance in t...
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doaj-2ec087d33fba4e25881d119727bc35332021-03-29T19:57:24ZengIEEEIEEE Access2169-35362017-01-015257592578010.1109/ACCESS.2017.27717418101459Enhancing the Harmony Search Algorithm Performance on Constrained Numerical OptimizationEdgar Alfredo Portilla-Flores0https://orcid.org/0000-0002-8951-1346Alvaro Sanchez-Marquez1Leticia Flores-Pulido2Eduardo Vega-Alvarado3https://orcid.org/0000-0001-9464-7996Maria Barbara Calva Yanez4Jorge Alexander Aponte-Rodriguez5Paola Andrea Nino-Suarez6Unidad Profesional Adolfo López Mateos, Instituto Politécnico Nacional-CIDETEC, Ciudad de México, C.P., MéxicoFacultad de Ciencias Básicas, Ingeniería y Tecnología, Universidad Autónoma de Tlaxcala, Tlaxcala, C.P., MéxicoFacultad de Ciencias Básicas, Ingeniería y Tecnología, Universidad Autónoma de Tlaxcala, Tlaxcala, C.P., MéxicoUnidad Profesional Adolfo López Mateos, Instituto Politécnico Nacional-CIDETEC, Ciudad de México, C.P., MéxicoInstituto Politécnico Nacional-ESIME-AZC-SEPI, Ciudad de México, C.P., MéxicoUniversidad Militar Nueva Granada, Bogotá, ColombiaInstituto Politécnico Nacional-ESIME-AZC-SEPI, Ciudad de México, C.P., MéxicoIn this paper, an improved harmony search (ImHS) algorithm is presented. HS is a simple but efficient metaheuristic method explored in recent literature, that simulates the process of musical improvisation. Two modifications for parameter tuning are proposed to enhance the algorithm performance in the solution of constrained numerical optimization problems, maintaining the simplicity of its original design. Metaheuristics are methods for solving optimization problems, and are based in two processes: exploration (diversification) and exploitation (intensification). The proposed modifications improve both processes in HS, without breaking their balance. A well-known ideal problem set was used as a reference to compare the efficiency of the developed algorithm ImHS with HS and three of its most successful variants, and also with two other metaheuristics of different nature, artificial bee colony (ABC) and modified ABC (MABC). Various techniques were applied to evaluate the algorithm performance with the proposed modifications, in order to validate the reliability of the comparison. In most case studies, ImHS far surpassed the results of HS and ABC, also improving the performance of the selected variants. Additionally, its results reached a similar quality than the obtained with MABC but with a significantly lower computational cost, suggesting that it can be a useful tool for solving real-world optimization problems if they are modeled as constrained numerical cases.https://ieeexplore.ieee.org/document/8101459/Harmony searchnumerical optimizationmetaheuristics |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Edgar Alfredo Portilla-Flores Alvaro Sanchez-Marquez Leticia Flores-Pulido Eduardo Vega-Alvarado Maria Barbara Calva Yanez Jorge Alexander Aponte-Rodriguez Paola Andrea Nino-Suarez |
spellingShingle |
Edgar Alfredo Portilla-Flores Alvaro Sanchez-Marquez Leticia Flores-Pulido Eduardo Vega-Alvarado Maria Barbara Calva Yanez Jorge Alexander Aponte-Rodriguez Paola Andrea Nino-Suarez Enhancing the Harmony Search Algorithm Performance on Constrained Numerical Optimization IEEE Access Harmony search numerical optimization metaheuristics |
author_facet |
Edgar Alfredo Portilla-Flores Alvaro Sanchez-Marquez Leticia Flores-Pulido Eduardo Vega-Alvarado Maria Barbara Calva Yanez Jorge Alexander Aponte-Rodriguez Paola Andrea Nino-Suarez |
author_sort |
Edgar Alfredo Portilla-Flores |
title |
Enhancing the Harmony Search Algorithm Performance on Constrained Numerical Optimization |
title_short |
Enhancing the Harmony Search Algorithm Performance on Constrained Numerical Optimization |
title_full |
Enhancing the Harmony Search Algorithm Performance on Constrained Numerical Optimization |
title_fullStr |
Enhancing the Harmony Search Algorithm Performance on Constrained Numerical Optimization |
title_full_unstemmed |
Enhancing the Harmony Search Algorithm Performance on Constrained Numerical Optimization |
title_sort |
enhancing the harmony search algorithm performance on constrained numerical optimization |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2017-01-01 |
description |
In this paper, an improved harmony search (ImHS) algorithm is presented. HS is a simple but efficient metaheuristic method explored in recent literature, that simulates the process of musical improvisation. Two modifications for parameter tuning are proposed to enhance the algorithm performance in the solution of constrained numerical optimization problems, maintaining the simplicity of its original design. Metaheuristics are methods for solving optimization problems, and are based in two processes: exploration (diversification) and exploitation (intensification). The proposed modifications improve both processes in HS, without breaking their balance. A well-known ideal problem set was used as a reference to compare the efficiency of the developed algorithm ImHS with HS and three of its most successful variants, and also with two other metaheuristics of different nature, artificial bee colony (ABC) and modified ABC (MABC). Various techniques were applied to evaluate the algorithm performance with the proposed modifications, in order to validate the reliability of the comparison. In most case studies, ImHS far surpassed the results of HS and ABC, also improving the performance of the selected variants. Additionally, its results reached a similar quality than the obtained with MABC but with a significantly lower computational cost, suggesting that it can be a useful tool for solving real-world optimization problems if they are modeled as constrained numerical cases. |
topic |
Harmony search numerical optimization metaheuristics |
url |
https://ieeexplore.ieee.org/document/8101459/ |
work_keys_str_mv |
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