A new adaptive mutation simulated annealing algorithm: application to the study of pure and mixed Pt–Pd clusters
Abstract In this article we would like to propose a modified simulated annealing procedure termed as adaptive mutation simulated annealing. In this, the parameters within the optimization scheme is dynamically updated keeping in view the requirements of the parameter values needed for efficient and...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Biring, Shyamal Kumar [verfasserIn] Sharma, Rahul [verfasserIn] Chaudhury, Pinaki [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2013 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Journal of mathematical chemistry - Dordrecht [u.a.] : Springer Science + Business Media B.V., 1987, 52(2013), 1 vom: 09. Okt., Seite 368-397 |
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| Übergeordnetes Werk: |
volume:52 ; year:2013 ; number:1 ; day:09 ; month:10 ; pages:368-397 |
| Links: |
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| DOI / URN: |
10.1007/s10910-013-0268-y |
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| Katalog-ID: |
SPR014550806 |
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| 245 | 1 | 2 | |a A new adaptive mutation simulated annealing algorithm: application to the study of pure and mixed Pt–Pd clusters |
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| 520 | |a Abstract In this article we would like to propose a modified simulated annealing procedure termed as adaptive mutation simulated annealing. In this, the parameters within the optimization scheme is dynamically updated keeping in view the requirements of the parameter values needed for efficient and unequivocal identification of the global minimum in a really rugged multiple minima surface. We apply this procedure to the problem of finding out the global minimum structures of pure Platinum and Palladium clusters as well as the mixed Pt–Pd ones (for cluster sizes upto 60), where the interactions among the constituents of the cluster are defined by the many body empirical Gupta potential. Once the structures are obtained, we try to find out the sizes for which the clusters possess greater stability. These so called magic numbers are compared with existing literature values. To test the efficiency of the proposed procedure we compare the results with conventional simulated annealing. We also analyse in detail and calculate various statistical properties and their evolution during the adaptive mutation simulated annealing run. This in-depth analysis gives an insight into why the current procedure outperforms the conventional simulated annealing. | ||
| 650 | 4 | |a Simulated annealing |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Adaptive simulated annealing |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Atomic cluster |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Bimetallic cluster |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Platinum–Palladium cluster |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Sharma, Rahul |e verfasserin |4 aut | |
| 700 | 1 | |a Chaudhury, Pinaki |e verfasserin |4 aut | |
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10.1007/s10910-013-0268-y doi (DE-627)SPR014550806 (SPR)s10910-013-0268-y-e DE-627 ger DE-627 rakwb eng 540 510 ASE 35.05 bkl Biring, Shyamal Kumar verfasserin aut A new adaptive mutation simulated annealing algorithm: application to the study of pure and mixed Pt–Pd clusters 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In this article we would like to propose a modified simulated annealing procedure termed as adaptive mutation simulated annealing. In this, the parameters within the optimization scheme is dynamically updated keeping in view the requirements of the parameter values needed for efficient and unequivocal identification of the global minimum in a really rugged multiple minima surface. We apply this procedure to the problem of finding out the global minimum structures of pure Platinum and Palladium clusters as well as the mixed Pt–Pd ones (for cluster sizes upto 60), where the interactions among the constituents of the cluster are defined by the many body empirical Gupta potential. Once the structures are obtained, we try to find out the sizes for which the clusters possess greater stability. These so called magic numbers are compared with existing literature values. To test the efficiency of the proposed procedure we compare the results with conventional simulated annealing. We also analyse in detail and calculate various statistical properties and their evolution during the adaptive mutation simulated annealing run. This in-depth analysis gives an insight into why the current procedure outperforms the conventional simulated annealing. Simulated annealing (dpeaa)DE-He213 Adaptive simulated annealing (dpeaa)DE-He213 Atomic cluster (dpeaa)DE-He213 Bimetallic cluster (dpeaa)DE-He213 Platinum–Palladium cluster (dpeaa)DE-He213 Sharma, Rahul verfasserin aut Chaudhury, Pinaki verfasserin aut Enthalten in Journal of mathematical chemistry Dordrecht [u.a.] : Springer Science + Business Media B.V., 1987 52(2013), 1 vom: 09. Okt., Seite 368-397 (DE-627)30246879X (DE-600)1491406-2 1572-8897 nnns volume:52 year:2013 number:1 day:09 month:10 pages:368-397 https://dx.doi.org/10.1007/s10910-013-0268-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA SSG-OPC-MAT SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 35.05 ASE AR 52 2013 1 09 10 368-397 |
| spelling |
10.1007/s10910-013-0268-y doi (DE-627)SPR014550806 (SPR)s10910-013-0268-y-e DE-627 ger DE-627 rakwb eng 540 510 ASE 35.05 bkl Biring, Shyamal Kumar verfasserin aut A new adaptive mutation simulated annealing algorithm: application to the study of pure and mixed Pt–Pd clusters 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In this article we would like to propose a modified simulated annealing procedure termed as adaptive mutation simulated annealing. In this, the parameters within the optimization scheme is dynamically updated keeping in view the requirements of the parameter values needed for efficient and unequivocal identification of the global minimum in a really rugged multiple minima surface. We apply this procedure to the problem of finding out the global minimum structures of pure Platinum and Palladium clusters as well as the mixed Pt–Pd ones (for cluster sizes upto 60), where the interactions among the constituents of the cluster are defined by the many body empirical Gupta potential. Once the structures are obtained, we try to find out the sizes for which the clusters possess greater stability. These so called magic numbers are compared with existing literature values. To test the efficiency of the proposed procedure we compare the results with conventional simulated annealing. We also analyse in detail and calculate various statistical properties and their evolution during the adaptive mutation simulated annealing run. This in-depth analysis gives an insight into why the current procedure outperforms the conventional simulated annealing. Simulated annealing (dpeaa)DE-He213 Adaptive simulated annealing (dpeaa)DE-He213 Atomic cluster (dpeaa)DE-He213 Bimetallic cluster (dpeaa)DE-He213 Platinum–Palladium cluster (dpeaa)DE-He213 Sharma, Rahul verfasserin aut Chaudhury, Pinaki verfasserin aut Enthalten in Journal of mathematical chemistry Dordrecht [u.a.] : Springer Science + Business Media B.V., 1987 52(2013), 1 vom: 09. Okt., Seite 368-397 (DE-627)30246879X (DE-600)1491406-2 1572-8897 nnns volume:52 year:2013 number:1 day:09 month:10 pages:368-397 https://dx.doi.org/10.1007/s10910-013-0268-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA SSG-OPC-MAT SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 35.05 ASE AR 52 2013 1 09 10 368-397 |
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10.1007/s10910-013-0268-y doi (DE-627)SPR014550806 (SPR)s10910-013-0268-y-e DE-627 ger DE-627 rakwb eng 540 510 ASE 35.05 bkl Biring, Shyamal Kumar verfasserin aut A new adaptive mutation simulated annealing algorithm: application to the study of pure and mixed Pt–Pd clusters 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In this article we would like to propose a modified simulated annealing procedure termed as adaptive mutation simulated annealing. In this, the parameters within the optimization scheme is dynamically updated keeping in view the requirements of the parameter values needed for efficient and unequivocal identification of the global minimum in a really rugged multiple minima surface. We apply this procedure to the problem of finding out the global minimum structures of pure Platinum and Palladium clusters as well as the mixed Pt–Pd ones (for cluster sizes upto 60), where the interactions among the constituents of the cluster are defined by the many body empirical Gupta potential. Once the structures are obtained, we try to find out the sizes for which the clusters possess greater stability. These so called magic numbers are compared with existing literature values. To test the efficiency of the proposed procedure we compare the results with conventional simulated annealing. We also analyse in detail and calculate various statistical properties and their evolution during the adaptive mutation simulated annealing run. This in-depth analysis gives an insight into why the current procedure outperforms the conventional simulated annealing. Simulated annealing (dpeaa)DE-He213 Adaptive simulated annealing (dpeaa)DE-He213 Atomic cluster (dpeaa)DE-He213 Bimetallic cluster (dpeaa)DE-He213 Platinum–Palladium cluster (dpeaa)DE-He213 Sharma, Rahul verfasserin aut Chaudhury, Pinaki verfasserin aut Enthalten in Journal of mathematical chemistry Dordrecht [u.a.] : Springer Science + Business Media B.V., 1987 52(2013), 1 vom: 09. Okt., Seite 368-397 (DE-627)30246879X (DE-600)1491406-2 1572-8897 nnns volume:52 year:2013 number:1 day:09 month:10 pages:368-397 https://dx.doi.org/10.1007/s10910-013-0268-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA SSG-OPC-MAT SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 35.05 ASE AR 52 2013 1 09 10 368-397 |
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10.1007/s10910-013-0268-y doi (DE-627)SPR014550806 (SPR)s10910-013-0268-y-e DE-627 ger DE-627 rakwb eng 540 510 ASE 35.05 bkl Biring, Shyamal Kumar verfasserin aut A new adaptive mutation simulated annealing algorithm: application to the study of pure and mixed Pt–Pd clusters 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In this article we would like to propose a modified simulated annealing procedure termed as adaptive mutation simulated annealing. In this, the parameters within the optimization scheme is dynamically updated keeping in view the requirements of the parameter values needed for efficient and unequivocal identification of the global minimum in a really rugged multiple minima surface. We apply this procedure to the problem of finding out the global minimum structures of pure Platinum and Palladium clusters as well as the mixed Pt–Pd ones (for cluster sizes upto 60), where the interactions among the constituents of the cluster are defined by the many body empirical Gupta potential. Once the structures are obtained, we try to find out the sizes for which the clusters possess greater stability. These so called magic numbers are compared with existing literature values. To test the efficiency of the proposed procedure we compare the results with conventional simulated annealing. We also analyse in detail and calculate various statistical properties and their evolution during the adaptive mutation simulated annealing run. This in-depth analysis gives an insight into why the current procedure outperforms the conventional simulated annealing. Simulated annealing (dpeaa)DE-He213 Adaptive simulated annealing (dpeaa)DE-He213 Atomic cluster (dpeaa)DE-He213 Bimetallic cluster (dpeaa)DE-He213 Platinum–Palladium cluster (dpeaa)DE-He213 Sharma, Rahul verfasserin aut Chaudhury, Pinaki verfasserin aut Enthalten in Journal of mathematical chemistry Dordrecht [u.a.] : Springer Science + Business Media B.V., 1987 52(2013), 1 vom: 09. Okt., Seite 368-397 (DE-627)30246879X (DE-600)1491406-2 1572-8897 nnns volume:52 year:2013 number:1 day:09 month:10 pages:368-397 https://dx.doi.org/10.1007/s10910-013-0268-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA SSG-OPC-MAT SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 35.05 ASE AR 52 2013 1 09 10 368-397 |
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10.1007/s10910-013-0268-y doi (DE-627)SPR014550806 (SPR)s10910-013-0268-y-e DE-627 ger DE-627 rakwb eng 540 510 ASE 35.05 bkl Biring, Shyamal Kumar verfasserin aut A new adaptive mutation simulated annealing algorithm: application to the study of pure and mixed Pt–Pd clusters 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In this article we would like to propose a modified simulated annealing procedure termed as adaptive mutation simulated annealing. In this, the parameters within the optimization scheme is dynamically updated keeping in view the requirements of the parameter values needed for efficient and unequivocal identification of the global minimum in a really rugged multiple minima surface. We apply this procedure to the problem of finding out the global minimum structures of pure Platinum and Palladium clusters as well as the mixed Pt–Pd ones (for cluster sizes upto 60), where the interactions among the constituents of the cluster are defined by the many body empirical Gupta potential. Once the structures are obtained, we try to find out the sizes for which the clusters possess greater stability. These so called magic numbers are compared with existing literature values. To test the efficiency of the proposed procedure we compare the results with conventional simulated annealing. We also analyse in detail and calculate various statistical properties and their evolution during the adaptive mutation simulated annealing run. This in-depth analysis gives an insight into why the current procedure outperforms the conventional simulated annealing. Simulated annealing (dpeaa)DE-He213 Adaptive simulated annealing (dpeaa)DE-He213 Atomic cluster (dpeaa)DE-He213 Bimetallic cluster (dpeaa)DE-He213 Platinum–Palladium cluster (dpeaa)DE-He213 Sharma, Rahul verfasserin aut Chaudhury, Pinaki verfasserin aut Enthalten in Journal of mathematical chemistry Dordrecht [u.a.] : Springer Science + Business Media B.V., 1987 52(2013), 1 vom: 09. Okt., Seite 368-397 (DE-627)30246879X (DE-600)1491406-2 1572-8897 nnns volume:52 year:2013 number:1 day:09 month:10 pages:368-397 https://dx.doi.org/10.1007/s10910-013-0268-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA SSG-OPC-MAT SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 35.05 ASE AR 52 2013 1 09 10 368-397 |
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Biring, Shyamal Kumar @@aut@@ Sharma, Rahul @@aut@@ Chaudhury, Pinaki @@aut@@ |
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In this, the parameters within the optimization scheme is dynamically updated keeping in view the requirements of the parameter values needed for efficient and unequivocal identification of the global minimum in a really rugged multiple minima surface. We apply this procedure to the problem of finding out the global minimum structures of pure Platinum and Palladium clusters as well as the mixed Pt–Pd ones (for cluster sizes upto 60), where the interactions among the constituents of the cluster are defined by the many body empirical Gupta potential. Once the structures are obtained, we try to find out the sizes for which the clusters possess greater stability. These so called magic numbers are compared with existing literature values. To test the efficiency of the proposed procedure we compare the results with conventional simulated annealing. We also analyse in detail and calculate various statistical properties and their evolution during the adaptive mutation simulated annealing run. This in-depth analysis gives an insight into why the current procedure outperforms the conventional simulated annealing.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Simulated annealing</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Adaptive simulated annealing</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Atomic cluster</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Bimetallic cluster</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Platinum–Palladium cluster</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Sharma, Rahul</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Chaudhury, Pinaki</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Journal of mathematical chemistry</subfield><subfield code="d">Dordrecht [u.a.] : Springer Science + Business Media B.V., 1987</subfield><subfield code="g">52(2013), 1 vom: 09. 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540 510 ASE 35.05 bkl A new adaptive mutation simulated annealing algorithm: application to the study of pure and mixed Pt–Pd clusters Simulated annealing (dpeaa)DE-He213 Adaptive simulated annealing (dpeaa)DE-He213 Atomic cluster (dpeaa)DE-He213 Bimetallic cluster (dpeaa)DE-He213 Platinum–Palladium cluster (dpeaa)DE-He213 |
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new adaptive mutation simulated annealing algorithm: application to the study of pure and mixed pt–pd clusters |
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A new adaptive mutation simulated annealing algorithm: application to the study of pure and mixed Pt–Pd clusters |
| abstract |
Abstract In this article we would like to propose a modified simulated annealing procedure termed as adaptive mutation simulated annealing. In this, the parameters within the optimization scheme is dynamically updated keeping in view the requirements of the parameter values needed for efficient and unequivocal identification of the global minimum in a really rugged multiple minima surface. We apply this procedure to the problem of finding out the global minimum structures of pure Platinum and Palladium clusters as well as the mixed Pt–Pd ones (for cluster sizes upto 60), where the interactions among the constituents of the cluster are defined by the many body empirical Gupta potential. Once the structures are obtained, we try to find out the sizes for which the clusters possess greater stability. These so called magic numbers are compared with existing literature values. To test the efficiency of the proposed procedure we compare the results with conventional simulated annealing. We also analyse in detail and calculate various statistical properties and their evolution during the adaptive mutation simulated annealing run. This in-depth analysis gives an insight into why the current procedure outperforms the conventional simulated annealing. |
| abstractGer |
Abstract In this article we would like to propose a modified simulated annealing procedure termed as adaptive mutation simulated annealing. In this, the parameters within the optimization scheme is dynamically updated keeping in view the requirements of the parameter values needed for efficient and unequivocal identification of the global minimum in a really rugged multiple minima surface. We apply this procedure to the problem of finding out the global minimum structures of pure Platinum and Palladium clusters as well as the mixed Pt–Pd ones (for cluster sizes upto 60), where the interactions among the constituents of the cluster are defined by the many body empirical Gupta potential. Once the structures are obtained, we try to find out the sizes for which the clusters possess greater stability. These so called magic numbers are compared with existing literature values. To test the efficiency of the proposed procedure we compare the results with conventional simulated annealing. We also analyse in detail and calculate various statistical properties and their evolution during the adaptive mutation simulated annealing run. This in-depth analysis gives an insight into why the current procedure outperforms the conventional simulated annealing. |
| abstract_unstemmed |
Abstract In this article we would like to propose a modified simulated annealing procedure termed as adaptive mutation simulated annealing. In this, the parameters within the optimization scheme is dynamically updated keeping in view the requirements of the parameter values needed for efficient and unequivocal identification of the global minimum in a really rugged multiple minima surface. We apply this procedure to the problem of finding out the global minimum structures of pure Platinum and Palladium clusters as well as the mixed Pt–Pd ones (for cluster sizes upto 60), where the interactions among the constituents of the cluster are defined by the many body empirical Gupta potential. Once the structures are obtained, we try to find out the sizes for which the clusters possess greater stability. These so called magic numbers are compared with existing literature values. To test the efficiency of the proposed procedure we compare the results with conventional simulated annealing. We also analyse in detail and calculate various statistical properties and their evolution during the adaptive mutation simulated annealing run. This in-depth analysis gives an insight into why the current procedure outperforms the conventional simulated annealing. |
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| title_short |
A new adaptive mutation simulated annealing algorithm: application to the study of pure and mixed Pt–Pd clusters |
| url |
https://dx.doi.org/10.1007/s10910-013-0268-y |
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| author2 |
Sharma, Rahul Chaudhury, Pinaki |
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Sharma, Rahul Chaudhury, Pinaki |
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| doi_str |
10.1007/s10910-013-0268-y |
| up_date |
2024-07-04T02:13:21.701Z |
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| score |
7.3996487 |