VARIANCE-BASED HARMONY SEARCH ALGORITHM FOR UNIMODAL AND MULTIMODAL OPTIMIZATION PROBLEMS WITH APPLICATION TO CLUSTERING
This article presents a novel variance-based harmony search algorithm (VHS) for solving optimization problems. VHS incorporates the concepts borrowed from the invasive weed optimization technique to improve the performance of the harmony search algorithm (HS). This eliminates the main problem of con...
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| Vydáno v: | Cybernetics and systems Ročník 45; číslo 6; s. 486 - 511 |
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| Hlavní autoři: | , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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Taylor & Francis Group
18.08.2014
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| ISSN: | 0196-9722, 1087-6553 |
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| Abstract | This article presents a novel variance-based harmony search algorithm (VHS) for solving optimization problems. VHS incorporates the concepts borrowed from the invasive weed optimization technique to improve the performance of the harmony search algorithm (HS). This eliminates the main problem of constant parameter setting in the algorithm proposed recently and named as explorative HS. It uses the variance of a current population as well as presents a solution vector to improvise the harmony memory. In addition, the dynamic pitch adjustment operator is used to avoid solution oscillation. The proposed algorithm is evaluated on 14 standard benchmark functions of various characteristics. The performance of the proposed algorithm is investigated and compared with classical HS, an improved version of HS, the global best HS, self-adaptive HS, explorative HS, and the recently proposed state-of-art gravitational search algorithm. Experimental results reveal that the proposed algorithm outperforms the above-mentioned approaches. The effects of scalability, noise, harmony memory size, and harmony memory consideration rate have also been investigated with the proposed algorithm. The proposed algorithm is then employed for a data clustering problem. Four real-life datasets selected from the UCI machine learning repository have been used. The results indicate that the VHS-based clustering outperforms the existing well-known clustering algorithms. |
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| AbstractList | This article presents a novel variance-based harmony search algorithm (VHS) for solving optimization problems. VHS incorporates the concepts borrowed from the invasive weed optimization technique to improve the performance of the harmony search algorithm (HS). This eliminates the main problem of constant parameter setting in the algorithm proposed recently and named as explorative HS. It uses the variance of a current population as well as presents a solution vector to improvise the harmony memory. In addition, the dynamic pitch adjustment operator is used to avoid solution oscillation. The proposed algorithm is evaluated on 14 standard benchmark functions of various characteristics. The performance of the proposed algorithm is investigated and compared with classical HS, an improved version of HS, the global best HS, self-adaptive HS, explorative HS, and the recently proposed state-of-art gravitational search algorithm. Experimental results reveal that the proposed algorithm outperforms the above-mentioned approaches. The effects of scalability, noise, harmony memory size, and harmony memory consideration rate have also been investigated with the proposed algorithm. The proposed algorithm is then employed for a data clustering problem. Four real-life datasets selected from the UCI machine learning repository have been used. The results indicate that the VHS-based clustering outperforms the existing well-known clustering algorithms. |
| Author | Chhabra, Jitender Kumar Kumar, Dinesh Kumar, Vijay |
| Author_xml | – sequence: 1 givenname: Vijay surname: Kumar fullname: Kumar, Vijay email: vijaykumarchahar@gmail.com organization: Computer Science and Engineering Department , JCDMCOE – sequence: 2 givenname: Jitender Kumar surname: Chhabra fullname: Chhabra, Jitender Kumar organization: Computer Engineering Department , National Institute of Technology – sequence: 3 givenname: Dinesh surname: Kumar fullname: Kumar, Dinesh organization: Computer Science and Engineering Department , GJUS&T |
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| CitedBy_id | crossref_primary_10_1016_j_advengsoft_2017_05_014 crossref_primary_10_1016_j_cmpb_2019_105091 crossref_primary_10_3390_s22176420 crossref_primary_10_3390_app10113827 crossref_primary_10_1016_j_eswa_2023_119954 crossref_primary_10_1002_dac_5300 crossref_primary_10_1155_2021_5594267 crossref_primary_10_1016_j_advengsoft_2017_05_008 crossref_primary_10_1016_j_advengsoft_2017_07_002 crossref_primary_10_3233_JIFS_232295 crossref_primary_10_1007_s12652_020_02580_0 crossref_primary_10_1080_0952813X_2017_1421267 |
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| Title | VARIANCE-BASED HARMONY SEARCH ALGORITHM FOR UNIMODAL AND MULTIMODAL OPTIMIZATION PROBLEMS WITH APPLICATION TO CLUSTERING |
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