Real-Valued Constraint Optimization with ICHEA

Anurag Sharma, Dharmendra Sharma

Research output: A Conference proceeding or a Chapter in BookConference contribution

3 Citations (Scopus)

Abstract

Intelligent constraint handling evolutionary algorithm (ICHEA) is a recently proposed variation of evolutionary algorithm (EA) that solves realvalued constraint satisfaction problems (CSPs) efficiently [20]. ICHEA has ability to extract and exploit information from constraints that guides its evolutionary search operators in contrast to traditional EAs that are ‘blind’ to constraints. Even its efficacy to solve CSPs it was not implemented to handle constraint optimization problems (COPs). This paper proposes an enhancement to ICHEA to solve real-valued COPs. The presented approach demonstrates very competitive results with other state-of-the-art approaches in terms of quality of solutions on well-known benchmark test problems.
Original languageEnglish
Title of host publicationInternational Conference on Neural Information Processing (ICONIP 2012)
Subtitle of host publicationLecture Notes in Computer Science
EditorsT Huang, Zeng Zhigang, C Li, C. S. Leung
Place of PublicationGermany
PublisherSpringer
Pages406-416
Number of pages11
Volume7665
ISBN (Electronic)9783642344879
ISBN (Print)9783642344862
DOIs
Publication statusPublished - 2012
Event19th International Conference on Neural Information Processing 2012 - Doha, Doha, Qatar
Duration: 12 Nov 201215 Nov 2012

Conference

Conference19th International Conference on Neural Information Processing 2012
CountryQatar
CityDoha
Period12/11/1215/11/12

Fingerprint

Evolutionary algorithms
Constraint satisfaction problems

Cite this

Sharma, A., & Sharma, D. (2012). Real-Valued Constraint Optimization with ICHEA. In T. Huang, Z. Zhigang, C. Li, & C. S. Leung (Eds.), International Conference on Neural Information Processing (ICONIP 2012): Lecture Notes in Computer Science (Vol. 7665, pp. 406-416). Germany: Springer. https://doi.org/10.1007/978-3-642-34487-9_50
Sharma, Anurag ; Sharma, Dharmendra. / Real-Valued Constraint Optimization with ICHEA. International Conference on Neural Information Processing (ICONIP 2012): Lecture Notes in Computer Science. editor / T Huang ; Zeng Zhigang ; C Li ; C. S. Leung. Vol. 7665 Germany : Springer, 2012. pp. 406-416
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abstract = "Intelligent constraint handling evolutionary algorithm (ICHEA) is a recently proposed variation of evolutionary algorithm (EA) that solves realvalued constraint satisfaction problems (CSPs) efficiently [20]. ICHEA has ability to extract and exploit information from constraints that guides its evolutionary search operators in contrast to traditional EAs that are ‘blind’ to constraints. Even its efficacy to solve CSPs it was not implemented to handle constraint optimization problems (COPs). This paper proposes an enhancement to ICHEA to solve real-valued COPs. The presented approach demonstrates very competitive results with other state-of-the-art approaches in terms of quality of solutions on well-known benchmark test problems.",
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Sharma, A & Sharma, D 2012, Real-Valued Constraint Optimization with ICHEA. in T Huang, Z Zhigang, C Li & CS Leung (eds), International Conference on Neural Information Processing (ICONIP 2012): Lecture Notes in Computer Science. vol. 7665, Springer, Germany, pp. 406-416, 19th International Conference on Neural Information Processing 2012, Doha, Qatar, 12/11/12. https://doi.org/10.1007/978-3-642-34487-9_50

Real-Valued Constraint Optimization with ICHEA. / Sharma, Anurag; Sharma, Dharmendra.

International Conference on Neural Information Processing (ICONIP 2012): Lecture Notes in Computer Science. ed. / T Huang; Zeng Zhigang; C Li; C. S. Leung. Vol. 7665 Germany : Springer, 2012. p. 406-416.

Research output: A Conference proceeding or a Chapter in BookConference contribution

TY - GEN

T1 - Real-Valued Constraint Optimization with ICHEA

AU - Sharma, Anurag

AU - Sharma, Dharmendra

PY - 2012

Y1 - 2012

N2 - Intelligent constraint handling evolutionary algorithm (ICHEA) is a recently proposed variation of evolutionary algorithm (EA) that solves realvalued constraint satisfaction problems (CSPs) efficiently [20]. ICHEA has ability to extract and exploit information from constraints that guides its evolutionary search operators in contrast to traditional EAs that are ‘blind’ to constraints. Even its efficacy to solve CSPs it was not implemented to handle constraint optimization problems (COPs). This paper proposes an enhancement to ICHEA to solve real-valued COPs. The presented approach demonstrates very competitive results with other state-of-the-art approaches in terms of quality of solutions on well-known benchmark test problems.

AB - Intelligent constraint handling evolutionary algorithm (ICHEA) is a recently proposed variation of evolutionary algorithm (EA) that solves realvalued constraint satisfaction problems (CSPs) efficiently [20]. ICHEA has ability to extract and exploit information from constraints that guides its evolutionary search operators in contrast to traditional EAs that are ‘blind’ to constraints. Even its efficacy to solve CSPs it was not implemented to handle constraint optimization problems (COPs). This paper proposes an enhancement to ICHEA to solve real-valued COPs. The presented approach demonstrates very competitive results with other state-of-the-art approaches in terms of quality of solutions on well-known benchmark test problems.

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KW - ICHEA

KW - Evolutionary algorithms

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SN - 9783642344862

VL - 7665

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BT - International Conference on Neural Information Processing (ICONIP 2012)

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Sharma A, Sharma D. Real-Valued Constraint Optimization with ICHEA. In Huang T, Zhigang Z, Li C, Leung CS, editors, International Conference on Neural Information Processing (ICONIP 2012): Lecture Notes in Computer Science. Vol. 7665. Germany: Springer. 2012. p. 406-416 https://doi.org/10.1007/978-3-642-34487-9_50