A Generalized Framework for Multi-objective-based Constraint Handling Technique
Abstract This paper introduces a novel approach to handling constraints in multi-objective optimization problems by treating constraints as objectives. Our study consists of three main contributions. First, we present a generalized framework for multi-objective-based constraint handling techniques,...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Dam, Tien Minh [verfasserIn] Truong, Long Viet [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2024 |
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| Schlagwörter: |
Constrained multi-objective evolutionary algorithm constrained multi-objective optimization problem constraint handling techniques |
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| Anmerkung: |
© ICROS, KIEE and Springer 2024 |
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| Übergeordnetes Werk: |
Enthalten in: International journal of control, automation, and systems - Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers, 2009, 22(2024), 10 vom: Okt., Seite 3240-3252 |
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| Übergeordnetes Werk: |
volume:22 ; year:2024 ; number:10 ; month:10 ; pages:3240-3252 |
| Links: |
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| DOI / URN: |
10.1007/s12555-024-0445-8 |
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| Katalog-ID: |
SPR057687838 |
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| 520 | |a Abstract This paper introduces a novel approach to handling constraints in multi-objective optimization problems by treating constraints as objectives. Our study consists of three main contributions. First, we present a generalized framework for multi-objective-based constraint handling techniques, which integrates multi-objective-based methods with the constraint dominance principle. This framework systematically incorporates various aspects of constraint violations into the objective function, enhancing optimization strategies. Second, we propose the constraint violation ratio, a metric that uses a constraint weight vector to quantify the severity of violations. Third, we develop the constraint diversity factor, an adaptive version of the constraint weight vector, which adapts as the frequency of constraint violations changes. Extensive experimental evaluations validate the effectiveness of our methods, demonstrating their applicability across a wide range of constrained optimization scenarios. | ||
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| 650 | 4 | |a constrained multi-objective optimization problem |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a constraint as objectives |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a constraint handling techniques |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a generalized framework for constraint handling |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a metaheuristic optimization algorithm |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Truong, Long Viet |e verfasserin |0 (orcid)0009-0002-2213-4184 |4 aut | |
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10.1007/s12555-024-0445-8 doi (DE-627)SPR057687838 (SPR)s12555-024-0445-8-e DE-627 ger DE-627 rakwb eng 620 VZ 620 VZ 50.20 bkl 50.23 bkl Dam, Tien Minh verfasserin (orcid)0009-0006-7683-4476 aut A Generalized Framework for Multi-objective-based Constraint Handling Technique 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © ICROS, KIEE and Springer 2024 Abstract This paper introduces a novel approach to handling constraints in multi-objective optimization problems by treating constraints as objectives. Our study consists of three main contributions. First, we present a generalized framework for multi-objective-based constraint handling techniques, which integrates multi-objective-based methods with the constraint dominance principle. This framework systematically incorporates various aspects of constraint violations into the objective function, enhancing optimization strategies. Second, we propose the constraint violation ratio, a metric that uses a constraint weight vector to quantify the severity of violations. Third, we develop the constraint diversity factor, an adaptive version of the constraint weight vector, which adapts as the frequency of constraint violations changes. Extensive experimental evaluations validate the effectiveness of our methods, demonstrating their applicability across a wide range of constrained optimization scenarios. Constrained multi-objective evolutionary algorithm (dpeaa)DE-He213 constrained multi-objective optimization problem (dpeaa)DE-He213 constraint as objectives (dpeaa)DE-He213 constraint handling techniques (dpeaa)DE-He213 generalized framework for constraint handling (dpeaa)DE-He213 metaheuristic optimization algorithm (dpeaa)DE-He213 Truong, Long Viet verfasserin (orcid)0009-0002-2213-4184 aut Enthalten in International journal of control, automation, and systems Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers, 2009 22(2024), 10 vom: Okt., Seite 3240-3252 Online-Ressource (DE-627)59477926X (DE-600)2486545-X (DE-576)307016277 2005-4092 nnns volume:22 year:2024 number:10 month:10 pages:3240-3252 https://dx.doi.org/10.1007/s12555-024-0445-8 X:SPRINGER Resolving-System lizenzpflichtig Volltext SYSFLAG_0 GBV_SPRINGER 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_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 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_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_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 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_2118 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_2574 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 50.20 Automatisierungstechnik VZ 50.23 Regelungstechnik Steuerungstechnik VZ AR 22 2024 10 10 3240-3252 |
| spelling |
10.1007/s12555-024-0445-8 doi (DE-627)SPR057687838 (SPR)s12555-024-0445-8-e DE-627 ger DE-627 rakwb eng 620 VZ 620 VZ 50.20 bkl 50.23 bkl Dam, Tien Minh verfasserin (orcid)0009-0006-7683-4476 aut A Generalized Framework for Multi-objective-based Constraint Handling Technique 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © ICROS, KIEE and Springer 2024 Abstract This paper introduces a novel approach to handling constraints in multi-objective optimization problems by treating constraints as objectives. Our study consists of three main contributions. First, we present a generalized framework for multi-objective-based constraint handling techniques, which integrates multi-objective-based methods with the constraint dominance principle. This framework systematically incorporates various aspects of constraint violations into the objective function, enhancing optimization strategies. Second, we propose the constraint violation ratio, a metric that uses a constraint weight vector to quantify the severity of violations. Third, we develop the constraint diversity factor, an adaptive version of the constraint weight vector, which adapts as the frequency of constraint violations changes. Extensive experimental evaluations validate the effectiveness of our methods, demonstrating their applicability across a wide range of constrained optimization scenarios. Constrained multi-objective evolutionary algorithm (dpeaa)DE-He213 constrained multi-objective optimization problem (dpeaa)DE-He213 constraint as objectives (dpeaa)DE-He213 constraint handling techniques (dpeaa)DE-He213 generalized framework for constraint handling (dpeaa)DE-He213 metaheuristic optimization algorithm (dpeaa)DE-He213 Truong, Long Viet verfasserin (orcid)0009-0002-2213-4184 aut Enthalten in International journal of control, automation, and systems Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers, 2009 22(2024), 10 vom: Okt., Seite 3240-3252 Online-Ressource (DE-627)59477926X (DE-600)2486545-X (DE-576)307016277 2005-4092 nnns volume:22 year:2024 number:10 month:10 pages:3240-3252 https://dx.doi.org/10.1007/s12555-024-0445-8 X:SPRINGER Resolving-System lizenzpflichtig Volltext SYSFLAG_0 GBV_SPRINGER 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_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 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_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_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 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_2118 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_2574 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 50.20 Automatisierungstechnik VZ 50.23 Regelungstechnik Steuerungstechnik VZ AR 22 2024 10 10 3240-3252 |
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10.1007/s12555-024-0445-8 doi (DE-627)SPR057687838 (SPR)s12555-024-0445-8-e DE-627 ger DE-627 rakwb eng 620 VZ 620 VZ 50.20 bkl 50.23 bkl Dam, Tien Minh verfasserin (orcid)0009-0006-7683-4476 aut A Generalized Framework for Multi-objective-based Constraint Handling Technique 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © ICROS, KIEE and Springer 2024 Abstract This paper introduces a novel approach to handling constraints in multi-objective optimization problems by treating constraints as objectives. Our study consists of three main contributions. First, we present a generalized framework for multi-objective-based constraint handling techniques, which integrates multi-objective-based methods with the constraint dominance principle. This framework systematically incorporates various aspects of constraint violations into the objective function, enhancing optimization strategies. Second, we propose the constraint violation ratio, a metric that uses a constraint weight vector to quantify the severity of violations. Third, we develop the constraint diversity factor, an adaptive version of the constraint weight vector, which adapts as the frequency of constraint violations changes. Extensive experimental evaluations validate the effectiveness of our methods, demonstrating their applicability across a wide range of constrained optimization scenarios. Constrained multi-objective evolutionary algorithm (dpeaa)DE-He213 constrained multi-objective optimization problem (dpeaa)DE-He213 constraint as objectives (dpeaa)DE-He213 constraint handling techniques (dpeaa)DE-He213 generalized framework for constraint handling (dpeaa)DE-He213 metaheuristic optimization algorithm (dpeaa)DE-He213 Truong, Long Viet verfasserin (orcid)0009-0002-2213-4184 aut Enthalten in International journal of control, automation, and systems Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers, 2009 22(2024), 10 vom: Okt., Seite 3240-3252 Online-Ressource (DE-627)59477926X (DE-600)2486545-X (DE-576)307016277 2005-4092 nnns volume:22 year:2024 number:10 month:10 pages:3240-3252 https://dx.doi.org/10.1007/s12555-024-0445-8 X:SPRINGER Resolving-System lizenzpflichtig Volltext SYSFLAG_0 GBV_SPRINGER 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_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 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_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_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 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_2118 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_2574 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 50.20 Automatisierungstechnik VZ 50.23 Regelungstechnik Steuerungstechnik VZ AR 22 2024 10 10 3240-3252 |
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A Generalized Framework for Multi-objective-based Constraint Handling Technique |
| abstract |
Abstract This paper introduces a novel approach to handling constraints in multi-objective optimization problems by treating constraints as objectives. Our study consists of three main contributions. First, we present a generalized framework for multi-objective-based constraint handling techniques, which integrates multi-objective-based methods with the constraint dominance principle. This framework systematically incorporates various aspects of constraint violations into the objective function, enhancing optimization strategies. Second, we propose the constraint violation ratio, a metric that uses a constraint weight vector to quantify the severity of violations. Third, we develop the constraint diversity factor, an adaptive version of the constraint weight vector, which adapts as the frequency of constraint violations changes. Extensive experimental evaluations validate the effectiveness of our methods, demonstrating their applicability across a wide range of constrained optimization scenarios. © ICROS, KIEE and Springer 2024 |
| abstractGer |
Abstract This paper introduces a novel approach to handling constraints in multi-objective optimization problems by treating constraints as objectives. Our study consists of three main contributions. First, we present a generalized framework for multi-objective-based constraint handling techniques, which integrates multi-objective-based methods with the constraint dominance principle. This framework systematically incorporates various aspects of constraint violations into the objective function, enhancing optimization strategies. Second, we propose the constraint violation ratio, a metric that uses a constraint weight vector to quantify the severity of violations. Third, we develop the constraint diversity factor, an adaptive version of the constraint weight vector, which adapts as the frequency of constraint violations changes. Extensive experimental evaluations validate the effectiveness of our methods, demonstrating their applicability across a wide range of constrained optimization scenarios. © ICROS, KIEE and Springer 2024 |
| abstract_unstemmed |
Abstract This paper introduces a novel approach to handling constraints in multi-objective optimization problems by treating constraints as objectives. Our study consists of three main contributions. First, we present a generalized framework for multi-objective-based constraint handling techniques, which integrates multi-objective-based methods with the constraint dominance principle. This framework systematically incorporates various aspects of constraint violations into the objective function, enhancing optimization strategies. Second, we propose the constraint violation ratio, a metric that uses a constraint weight vector to quantify the severity of violations. Third, we develop the constraint diversity factor, an adaptive version of the constraint weight vector, which adapts as the frequency of constraint violations changes. Extensive experimental evaluations validate the effectiveness of our methods, demonstrating their applicability across a wide range of constrained optimization scenarios. © ICROS, KIEE and Springer 2024 |
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| title_short |
A Generalized Framework for Multi-objective-based Constraint Handling Technique |
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https://dx.doi.org/10.1007/s12555-024-0445-8 |
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Truong, Long Viet |
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| doi_str |
10.1007/s12555-024-0445-8 |
| up_date |
2024-10-06T07:42:36.051Z |
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| score |
7.398978 |