A New Method for Analyzing the Performance of the Harmony Search Algorithm

A harmony search (HS) algorithm for solving high-dimensional multimodal optimization problems (named DIHS) was proposed in 2015 and showed good performance, in which a dynamic-dimensionality-reduction strategy is employed to maintain a high update success rate of harmony memory (HM). However, an ext...

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Main Authors: Shouheng Tuo, Zong Woo Geem, Jin Hee Yoon
Format: Article
Language:English
Published: MDPI AG 2020-08-01
Series:Mathematics
Subjects:
Online Access:https://www.mdpi.com/2227-7390/8/9/1421
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author Shouheng Tuo
Zong Woo Geem
Jin Hee Yoon
author_facet Shouheng Tuo
Zong Woo Geem
Jin Hee Yoon
author_sort Shouheng Tuo
collection DOAJ
description A harmony search (HS) algorithm for solving high-dimensional multimodal optimization problems (named DIHS) was proposed in 2015 and showed good performance, in which a dynamic-dimensionality-reduction strategy is employed to maintain a high update success rate of harmony memory (HM). However, an extreme assumption was adopted in the DIHS that is not reasonable, and its analysis for the update success rate is not sufficiently accurate. In this study, we reanalyzed the update success rate of HS and now present a more valid method for analyzing the update success rate of HS. In the new analysis, take-k and take-all strategies that are employed to generate new solutions are compared to the update success rate, and the average convergence rate of algorithms is also analyzed. The experimental results demonstrate that the HS based on the take-k strategy is efficient and effective at solving some complex high-dimensional optimization problems.
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spelling doaj.art-2bfb1745e2614ee5ae029166c3721d252023-11-20T11:13:48ZengMDPI AGMathematics2227-73902020-08-0189142110.3390/math8091421A New Method for Analyzing the Performance of the Harmony Search AlgorithmShouheng Tuo0Zong Woo Geem1Jin Hee Yoon2School of Computer Science and Technology, Xi’an University of Posts and Telecommunications, Xi’an 710121, ChinaDepartment of Energy IT, Gachon University, Seongnam 13120, KoreaSchool of Mathematics and Statistics, Sejong University, Seoul 05006, KoreaA harmony search (HS) algorithm for solving high-dimensional multimodal optimization problems (named DIHS) was proposed in 2015 and showed good performance, in which a dynamic-dimensionality-reduction strategy is employed to maintain a high update success rate of harmony memory (HM). However, an extreme assumption was adopted in the DIHS that is not reasonable, and its analysis for the update success rate is not sufficiently accurate. In this study, we reanalyzed the update success rate of HS and now present a more valid method for analyzing the update success rate of HS. In the new analysis, take-k and take-all strategies that are employed to generate new solutions are compared to the update success rate, and the average convergence rate of algorithms is also analyzed. The experimental results demonstrate that the HS based on the take-k strategy is efficient and effective at solving some complex high-dimensional optimization problems.https://www.mdpi.com/2227-7390/8/9/1421harmony searchupdate success ratehigh-dimensional optimization problemtake-k strategytake-all strategy
spellingShingle Shouheng Tuo
Zong Woo Geem
Jin Hee Yoon
A New Method for Analyzing the Performance of the Harmony Search Algorithm
Mathematics
harmony search
update success rate
high-dimensional optimization problem
take-k strategy
take-all strategy
title A New Method for Analyzing the Performance of the Harmony Search Algorithm
title_full A New Method for Analyzing the Performance of the Harmony Search Algorithm
title_fullStr A New Method for Analyzing the Performance of the Harmony Search Algorithm
title_full_unstemmed A New Method for Analyzing the Performance of the Harmony Search Algorithm
title_short A New Method for Analyzing the Performance of the Harmony Search Algorithm
title_sort new method for analyzing the performance of the harmony search algorithm
topic harmony search
update success rate
high-dimensional optimization problem
take-k strategy
take-all strategy
url https://www.mdpi.com/2227-7390/8/9/1421
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