Solving Dynamic Constraint Optimization Problems Using ICHEA

Anurag Sharma; Dharmendra Sharma

doi:10.1007/978-3-642-34487-9_53

Solving Dynamic Constraint Optimization Problems Using ICHEA

Anurag Sharma, Dharmendra Sharma

Information Systems

Research output: A Conference proceeding or a Chapter in Book › Conference contribution › peer-review

5 Citations (Scopus)

Abstract

Many real-world constrained problems have a set of predefined static constraints that can be solved by evolutionary algorithms (EAs) whereas some problems have dynamic constraints that may change over time or may be received by the problem solver at run time. Recently there has been some interest in academic research for solving continuous dynamic constraint optimization problems (DCOPs) where some new benchmark problems have been proposed. Intelligent constraint handling evolutionary algorithm (ICHEA) is demonstrated to be a versatile constraints guided EA for continuous constrained problems which efficiently solves constraint satisfaction problems (CSPs) in [22], constraint optimization problems (COPs) in [23] and dynamic constraint satisfaction problems (DCSPs) in [24]. We investigate efficiency of ICHEA in solving benchmark DCOPs and compare and contrast its performance with other well-known EAs.

Original language	English
Title of host publication	International Conference on Neural Information Processing (ICONIP 2012)
Subtitle of host publication	Lecture Notes in Computer Science
Editors	Tingwen Huang, Zhigang Zeng, Chuandong Li, C.S. Leung
Place of Publication	Berlin
Publisher	Springer
Pages	434-444
Number of pages	11
Volume	7665
ISBN (Print)	9783642344862
DOIs	https://doi.org/10.1007/978-3-642-34487-9_53
Publication status	Published - 2012
Event	19th International Conference on Neural Information Processing 2012 - Doha, Doha, Qatar Duration: 12 Nov 2012 → 15 Nov 2012

Conference

Conference	19th International Conference on Neural Information Processing 2012
Country/Territory	Qatar
City	Doha
Period	12/11/12 → 15/11/12

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10.1007/978-3-642-34487-9_53

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title = "Solving Dynamic Constraint Optimization Problems Using ICHEA",

abstract = "Many real-world constrained problems have a set of predefined static constraints that can be solved by evolutionary algorithms (EAs) whereas some problems have dynamic constraints that may change over time or may be received by the problem solver at run time. Recently there has been some interest in academic research for solving continuous dynamic constraint optimization problems (DCOPs) where some new benchmark problems have been proposed. Intelligent constraint handling evolutionary algorithm (ICHEA) is demonstrated to be a versatile constraints guided EA for continuous constrained problems which efficiently solves constraint satisfaction problems (CSPs) in [22], constraint optimization problems (COPs) in [23] and dynamic constraint satisfaction problems (DCSPs) in [24]. We investigate efficiency of ICHEA in solving benchmark DCOPs and compare and contrast its performance with other well-known EAs.",

keywords = "Dynamic constraint optimization problem, Intelligent constraint handling evolutionary algorithm, Evolutionary algorithms, dynamic constraint satisfaction problems",

author = "Anurag Sharma and Dharmendra Sharma",

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note = "19th International Conference on Neural Information Processing 2012 ; Conference date: 12-11-2012 Through 15-11-2012",

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Sharma, A & Sharma, D 2012, Solving Dynamic Constraint Optimization Problems Using ICHEA. in T Huang, Z Zeng, C Li & CS Leung (eds), International Conference on Neural Information Processing (ICONIP 2012): Lecture Notes in Computer Science. vol. 7665, Springer, Berlin, pp. 434-444, 19th International Conference on Neural Information Processing 2012, Doha, Qatar, 12/11/12. https://doi.org/10.1007/978-3-642-34487-9_53

Solving Dynamic Constraint Optimization Problems Using ICHEA. / Sharma, Anurag; Sharma, Dharmendra.
International Conference on Neural Information Processing (ICONIP 2012): Lecture Notes in Computer Science. ed. / Tingwen Huang; Zhigang Zeng; Chuandong Li; C.S. Leung. Vol. 7665 Berlin: Springer, 2012. p. 434-444.

Research output: A Conference proceeding or a Chapter in Book › Conference contribution › peer-review

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T1 - Solving Dynamic Constraint Optimization Problems Using ICHEA

AU - Sharma, Anurag

AU - Sharma, Dharmendra

PY - 2012

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N2 - Many real-world constrained problems have a set of predefined static constraints that can be solved by evolutionary algorithms (EAs) whereas some problems have dynamic constraints that may change over time or may be received by the problem solver at run time. Recently there has been some interest in academic research for solving continuous dynamic constraint optimization problems (DCOPs) where some new benchmark problems have been proposed. Intelligent constraint handling evolutionary algorithm (ICHEA) is demonstrated to be a versatile constraints guided EA for continuous constrained problems which efficiently solves constraint satisfaction problems (CSPs) in [22], constraint optimization problems (COPs) in [23] and dynamic constraint satisfaction problems (DCSPs) in [24]. We investigate efficiency of ICHEA in solving benchmark DCOPs and compare and contrast its performance with other well-known EAs.

AB - Many real-world constrained problems have a set of predefined static constraints that can be solved by evolutionary algorithms (EAs) whereas some problems have dynamic constraints that may change over time or may be received by the problem solver at run time. Recently there has been some interest in academic research for solving continuous dynamic constraint optimization problems (DCOPs) where some new benchmark problems have been proposed. Intelligent constraint handling evolutionary algorithm (ICHEA) is demonstrated to be a versatile constraints guided EA for continuous constrained problems which efficiently solves constraint satisfaction problems (CSPs) in [22], constraint optimization problems (COPs) in [23] and dynamic constraint satisfaction problems (DCSPs) in [24]. We investigate efficiency of ICHEA in solving benchmark DCOPs and compare and contrast its performance with other well-known EAs.

KW - Dynamic constraint optimization problem

KW - Intelligent constraint handling evolutionary algorithm

KW - Evolutionary algorithms

KW - dynamic constraint satisfaction problems

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DO - 10.1007/978-3-642-34487-9_53

M3 - Conference contribution

SN - 9783642344862

VL - 7665

SP - 434

EP - 444

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

A2 - Huang, Tingwen

A2 - Zeng, Zhigang

A2 - Li, Chuandong

A2 - Leung, C.S.

PB - Springer

CY - Berlin

T2 - 19th International Conference on Neural Information Processing 2012

Y2 - 12 November 2012 through 15 November 2012

ER -

Solving Dynamic Constraint Optimization Problems Using ICHEA

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