Adaptive harmony search with best-based search strategy
Abstract Harmony search (HS) is a new evolutionary algorithm inspired by the process of music improvisation. During the past decade, HS has shown excellent performance in many fields. However, its search strategy often demonstrates insufficient exploitation ability when facing some complex practical...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Guo, Zhaolu [verfasserIn] Yang, Huogen [verfasserIn] Wang, Shenwen [verfasserIn] Zhou, Caiying [verfasserIn] Liu, Xiaosheng [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2016 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Soft Computing - Springer-Verlag, 2003, 22(2016), 4 vom: 03. Nov., Seite 1335-1349 |
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| Übergeordnetes Werk: |
volume:22 ; year:2016 ; number:4 ; day:03 ; month:11 ; pages:1335-1349 |
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| DOI / URN: |
10.1007/s00500-016-2424-3 |
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SPR006501397 |
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| 520 | |a Abstract Harmony search (HS) is a new evolutionary algorithm inspired by the process of music improvisation. During the past decade, HS has shown excellent performance in many fields. However, its search strategy often demonstrates insufficient exploitation ability when facing some complex practical problems. Moreover, the HS performance is significantly influenced by its control parameters. To enhance the search efficiency, an adaptive harmony search with best-based search strategy (ABHS) is proposed. In the search process, ABHS exploits the beneficial information from the global-best solution to improve the search ability, while it adaptively tunes its control parameters according to the feedback from the search process. Experiments are conducted on a set of classical test functions. The experimental results show that ABHS significantly enhances the search efficiency of HS. | ||
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10.1007/s00500-016-2424-3 doi (DE-627)SPR006501397 (SPR)s00500-016-2424-3-e DE-627 ger DE-627 rakwb eng Guo, Zhaolu verfasserin aut Adaptive harmony search with best-based search strategy 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Harmony search (HS) is a new evolutionary algorithm inspired by the process of music improvisation. During the past decade, HS has shown excellent performance in many fields. However, its search strategy often demonstrates insufficient exploitation ability when facing some complex practical problems. Moreover, the HS performance is significantly influenced by its control parameters. To enhance the search efficiency, an adaptive harmony search with best-based search strategy (ABHS) is proposed. In the search process, ABHS exploits the beneficial information from the global-best solution to improve the search ability, while it adaptively tunes its control parameters according to the feedback from the search process. Experiments are conducted on a set of classical test functions. The experimental results show that ABHS significantly enhances the search efficiency of HS. Evolutionary algorithm (dpeaa)DE-He213 Harmony search (dpeaa)DE-He213 Adaptive (dpeaa)DE-He213 Search strategy (dpeaa)DE-He213 Yang, Huogen verfasserin aut Wang, Shenwen verfasserin aut Zhou, Caiying verfasserin aut Liu, Xiaosheng verfasserin aut Enthalten in Soft Computing Springer-Verlag, 2003 22(2016), 4 vom: 03. Nov., Seite 1335-1349 (DE-627)SPR006469531 nnns volume:22 year:2016 number:4 day:03 month:11 pages:1335-1349 https://dx.doi.org/10.1007/s00500-016-2424-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER AR 22 2016 4 03 11 1335-1349 |
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10.1007/s00500-016-2424-3 doi (DE-627)SPR006501397 (SPR)s00500-016-2424-3-e DE-627 ger DE-627 rakwb eng Guo, Zhaolu verfasserin aut Adaptive harmony search with best-based search strategy 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Harmony search (HS) is a new evolutionary algorithm inspired by the process of music improvisation. During the past decade, HS has shown excellent performance in many fields. However, its search strategy often demonstrates insufficient exploitation ability when facing some complex practical problems. Moreover, the HS performance is significantly influenced by its control parameters. To enhance the search efficiency, an adaptive harmony search with best-based search strategy (ABHS) is proposed. In the search process, ABHS exploits the beneficial information from the global-best solution to improve the search ability, while it adaptively tunes its control parameters according to the feedback from the search process. Experiments are conducted on a set of classical test functions. The experimental results show that ABHS significantly enhances the search efficiency of HS. Evolutionary algorithm (dpeaa)DE-He213 Harmony search (dpeaa)DE-He213 Adaptive (dpeaa)DE-He213 Search strategy (dpeaa)DE-He213 Yang, Huogen verfasserin aut Wang, Shenwen verfasserin aut Zhou, Caiying verfasserin aut Liu, Xiaosheng verfasserin aut Enthalten in Soft Computing Springer-Verlag, 2003 22(2016), 4 vom: 03. Nov., Seite 1335-1349 (DE-627)SPR006469531 nnns volume:22 year:2016 number:4 day:03 month:11 pages:1335-1349 https://dx.doi.org/10.1007/s00500-016-2424-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER AR 22 2016 4 03 11 1335-1349 |
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10.1007/s00500-016-2424-3 doi (DE-627)SPR006501397 (SPR)s00500-016-2424-3-e DE-627 ger DE-627 rakwb eng Guo, Zhaolu verfasserin aut Adaptive harmony search with best-based search strategy 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Harmony search (HS) is a new evolutionary algorithm inspired by the process of music improvisation. During the past decade, HS has shown excellent performance in many fields. However, its search strategy often demonstrates insufficient exploitation ability when facing some complex practical problems. Moreover, the HS performance is significantly influenced by its control parameters. To enhance the search efficiency, an adaptive harmony search with best-based search strategy (ABHS) is proposed. In the search process, ABHS exploits the beneficial information from the global-best solution to improve the search ability, while it adaptively tunes its control parameters according to the feedback from the search process. Experiments are conducted on a set of classical test functions. The experimental results show that ABHS significantly enhances the search efficiency of HS. Evolutionary algorithm (dpeaa)DE-He213 Harmony search (dpeaa)DE-He213 Adaptive (dpeaa)DE-He213 Search strategy (dpeaa)DE-He213 Yang, Huogen verfasserin aut Wang, Shenwen verfasserin aut Zhou, Caiying verfasserin aut Liu, Xiaosheng verfasserin aut Enthalten in Soft Computing Springer-Verlag, 2003 22(2016), 4 vom: 03. Nov., Seite 1335-1349 (DE-627)SPR006469531 nnns volume:22 year:2016 number:4 day:03 month:11 pages:1335-1349 https://dx.doi.org/10.1007/s00500-016-2424-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER AR 22 2016 4 03 11 1335-1349 |
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10.1007/s00500-016-2424-3 doi (DE-627)SPR006501397 (SPR)s00500-016-2424-3-e DE-627 ger DE-627 rakwb eng Guo, Zhaolu verfasserin aut Adaptive harmony search with best-based search strategy 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Harmony search (HS) is a new evolutionary algorithm inspired by the process of music improvisation. During the past decade, HS has shown excellent performance in many fields. However, its search strategy often demonstrates insufficient exploitation ability when facing some complex practical problems. Moreover, the HS performance is significantly influenced by its control parameters. To enhance the search efficiency, an adaptive harmony search with best-based search strategy (ABHS) is proposed. In the search process, ABHS exploits the beneficial information from the global-best solution to improve the search ability, while it adaptively tunes its control parameters according to the feedback from the search process. Experiments are conducted on a set of classical test functions. The experimental results show that ABHS significantly enhances the search efficiency of HS. Evolutionary algorithm (dpeaa)DE-He213 Harmony search (dpeaa)DE-He213 Adaptive (dpeaa)DE-He213 Search strategy (dpeaa)DE-He213 Yang, Huogen verfasserin aut Wang, Shenwen verfasserin aut Zhou, Caiying verfasserin aut Liu, Xiaosheng verfasserin aut Enthalten in Soft Computing Springer-Verlag, 2003 22(2016), 4 vom: 03. Nov., Seite 1335-1349 (DE-627)SPR006469531 nnns volume:22 year:2016 number:4 day:03 month:11 pages:1335-1349 https://dx.doi.org/10.1007/s00500-016-2424-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER AR 22 2016 4 03 11 1335-1349 |
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Abstract Harmony search (HS) is a new evolutionary algorithm inspired by the process of music improvisation. During the past decade, HS has shown excellent performance in many fields. However, its search strategy often demonstrates insufficient exploitation ability when facing some complex practical problems. Moreover, the HS performance is significantly influenced by its control parameters. To enhance the search efficiency, an adaptive harmony search with best-based search strategy (ABHS) is proposed. In the search process, ABHS exploits the beneficial information from the global-best solution to improve the search ability, while it adaptively tunes its control parameters according to the feedback from the search process. Experiments are conducted on a set of classical test functions. The experimental results show that ABHS significantly enhances the search efficiency of HS. |
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Abstract Harmony search (HS) is a new evolutionary algorithm inspired by the process of music improvisation. During the past decade, HS has shown excellent performance in many fields. However, its search strategy often demonstrates insufficient exploitation ability when facing some complex practical problems. Moreover, the HS performance is significantly influenced by its control parameters. To enhance the search efficiency, an adaptive harmony search with best-based search strategy (ABHS) is proposed. In the search process, ABHS exploits the beneficial information from the global-best solution to improve the search ability, while it adaptively tunes its control parameters according to the feedback from the search process. Experiments are conducted on a set of classical test functions. The experimental results show that ABHS significantly enhances the search efficiency of HS. |
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Abstract Harmony search (HS) is a new evolutionary algorithm inspired by the process of music improvisation. During the past decade, HS has shown excellent performance in many fields. However, its search strategy often demonstrates insufficient exploitation ability when facing some complex practical problems. Moreover, the HS performance is significantly influenced by its control parameters. To enhance the search efficiency, an adaptive harmony search with best-based search strategy (ABHS) is proposed. In the search process, ABHS exploits the beneficial information from the global-best solution to improve the search ability, while it adaptively tunes its control parameters according to the feedback from the search process. Experiments are conducted on a set of classical test functions. The experimental results show that ABHS significantly enhances the search efficiency of HS. |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">SPR006501397</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20201124002855.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">201005s2016 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s00500-016-2424-3</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR006501397</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s00500-016-2424-3-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Guo, Zhaolu</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Adaptive harmony search with best-based search strategy</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2016</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Harmony search (HS) is a new evolutionary algorithm inspired by the process of music improvisation. During the past decade, HS has shown excellent performance in many fields. However, its search strategy often demonstrates insufficient exploitation ability when facing some complex practical problems. Moreover, the HS performance is significantly influenced by its control parameters. To enhance the search efficiency, an adaptive harmony search with best-based search strategy (ABHS) is proposed. In the search process, ABHS exploits the beneficial information from the global-best solution to improve the search ability, while it adaptively tunes its control parameters according to the feedback from the search process. Experiments are conducted on a set of classical test functions. 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Nov., Seite 1335-1349</subfield><subfield code="w">(DE-627)SPR006469531</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:22</subfield><subfield code="g">year:2016</subfield><subfield code="g">number:4</subfield><subfield code="g">day:03</subfield><subfield code="g">month:11</subfield><subfield code="g">pages:1335-1349</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://dx.doi.org/10.1007/s00500-016-2424-3</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_SPRINGER</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">22</subfield><subfield code="j">2016</subfield><subfield code="e">4</subfield><subfield code="b">03</subfield><subfield code="c">11</subfield><subfield code="h">1335-1349</subfield></datafield></record></collection>
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