Solving mixed-integer nonlinear programming problems using improved genetic algorithms

This paper proposes a method for solving mixed-integer nonlinear programming problems to achieve or approach the optimal solution by using modified genetic algorithms. The representation scheme covers both integer and real variables for solving mixed-integer nonlinear programming, nonlinear programm...

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Vydané v:	The Korean journal of chemical engineering Ročník 28; číslo 1; s. 32 - 40
Hlavní autori:	Wasanapradit, Tawan, Mukdasanit, Nalinee, Chaiyaratana, Nachol, Srinophakun, Thongchai
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Boston Springer US 01.01.2011 한국화학공학회
Predmet:	Biotechnology Catalysis Chemistry Chemistry and Materials Science Industrial Chemistry/Chemical Engineering Materials Science 화학공학 Mixed Integer Nonlinear Programming CPSS Modified Genetic Algorithms Genetic Algorithms Repairing Strategy
ISSN:	0256-1115, 1975-7220
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