A real coded genetic algorithm for solving integer and mixed integer optimization problems

In this paper, a real coded genetic algorithm named MI-LXPM is proposed for solving integer and mixed integer constrained optimization problems. The proposed algorithm is a suitably modified and extended version of the real coded genetic algorithm, LXPM, of Deep and Thakur [K. Deep, M. Thakur, A new...

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Vydané v:	Applied mathematics and computation Ročník 212; číslo 2; s. 505 - 518
Hlavní autori:	Deep, Kusum, Singh, Krishna Pratap, Kansal, M.L., Mohan, C.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Amsterdam Elsevier Inc 15.06.2009 Elsevier
Predmet:	Calculus of variations and optimal control Constrained optimization Exact sciences and technology Integer and mixed integer optimization problems Mathematical analysis Mathematics Numerical analysis Numerical analysis. Scientific computation Numerical methods in mathematical programming, optimization and calculus of variations Random search based techniques Real coded genetic algorithms Sciences and techniques of general use Integer and mixed integer optimization problems Real coded genetic algorithms Random search based techniques Constrained optimization Optimization method Penalty method Search algorithm Truncation Integer Integer and mixed integer optimization Numerical analysis Algorithm performance Genetic algorithm Applied mathematics Mixed problem Mathematical programming problems
ISSN:	0096-3003, 1873-5649
On-line prístup:	Získať plný text
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Abstract	In this paper, a real coded genetic algorithm named MI-LXPM is proposed for solving integer and mixed integer constrained optimization problems. The proposed algorithm is a suitably modified and extended version of the real coded genetic algorithm, LXPM, of Deep and Thakur [K. Deep, M. Thakur, A new crossover operator for real coded genetic algorithms, Applied Mathematics and Computation 188 (2007) 895–912; K. Deep, M. Thakur, A new mutation operator for real coded genetic algorithms, Applied Mathematics and Computation 193 (2007) 211–230]. The algorithm incorporates a special truncation procedure to handle integer restrictions on decision variables along with a parameter free penalty approach for handling constraints. Performance of the algorithm is tested on a set of twenty test problems selected from different sources in literature, and compared with the performance of an earlier application of genetic algorithm and also with random search based algorithm, RST2ANU, incorporating annealing concept. The proposed MI-LXPM outperforms both the algorithms in most of the cases which are considered.
AbstractList	In this paper, a real coded genetic algorithm named MI-LXPM is proposed for solving integer and mixed integer constrained optimization problems. The proposed algorithm is a suitably modified and extended version of the real coded genetic algorithm, LXPM, of Deep and Thakur [K. Deep, M. Thakur, A new crossover operator for real coded genetic algorithms, Applied Mathematics and Computation 188 (2007) 895–912; K. Deep, M. Thakur, A new mutation operator for real coded genetic algorithms, Applied Mathematics and Computation 193 (2007) 211–230]. The algorithm incorporates a special truncation procedure to handle integer restrictions on decision variables along with a parameter free penalty approach for handling constraints. Performance of the algorithm is tested on a set of twenty test problems selected from different sources in literature, and compared with the performance of an earlier application of genetic algorithm and also with random search based algorithm, RST2ANU, incorporating annealing concept. The proposed MI-LXPM outperforms both the algorithms in most of the cases which are considered.
Author	Deep, Kusum Singh, Krishna Pratap Mohan, C. Kansal, M.L.
Author_xml	– sequence: 1 givenname: Kusum surname: Deep fullname: Deep, Kusum email: kusumfma@iitr.ernet.in organization: Department of Mathematics, Indian Institute of Technology, Roorkee-247667, Uttarakhand, India – sequence: 2 givenname: Krishna Pratap surname: Singh fullname: Singh, Krishna Pratap email: kpsinghiitr@gmail.com organization: Department of Mathematics, Indian Institute of Technology, Roorkee-247667, Uttarakhand, India – sequence: 3 givenname: M.L. surname: Kansal fullname: Kansal, M.L. email: mlkgkfwt@iitr.ernet.in organization: Department of Water Resources Development and Management, Indian Institute of Technology, Roorkee-247667, Uttarakhand, India – sequence: 4 givenname: C. surname: Mohan fullname: Mohan, C. email: chander_mohan2@rediffmail.com organization: Ambala College of Engineering and Applied Research, Ambala, Haryana, India
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Keywords	Integer and mixed integer optimization problems Real coded genetic algorithms Random search based techniques Constrained optimization Optimization method Penalty method Search algorithm Truncation Integer Integer and mixed integer optimization Numerical analysis Algorithm performance Genetic algorithm Applied mathematics Mixed problem Mathematical programming problems
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Snippet	In this paper, a real coded genetic algorithm named MI-LXPM is proposed for solving integer and mixed integer constrained optimization problems. The proposed...
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SubjectTerms	Calculus of variations and optimal control Constrained optimization Exact sciences and technology Integer and mixed integer optimization problems Mathematical analysis Mathematics Numerical analysis Numerical analysis. Scientific computation Numerical methods in mathematical programming, optimization and calculus of variations Random search based techniques Real coded genetic algorithms Sciences and techniques of general use
Title	A real coded genetic algorithm for solving integer and mixed integer optimization problems
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