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Optimising a shaft's geometry by applying genetic algorithms

María Alejandra Guzmán / Alberto Delgado

Many engnieering design tasks involve optimising several conflicting goals; these types of problem are known as Multiobjective Optimisation Problems (MOPs). Evolutionary techniques have proved to be an effective tool for finding solutions to these MOPs during the last decade, Variations on the basic generic algorithm have been particulary proposed by different researchers for finding rapid optimal solutions to MOPs. The NSGA (Non-dominated Sorting Generic Algorithm) has been implemented in this paper for finding an optimal design for a shaft subjected to cyclic loads, the conflycting goals being minimum weight and minimum lateral deflection.

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Optimising a shaft's geometry by applying genetic algorithms

María Alejandra Guzmán / Alberto Delgado

Many engnieering design tasks involve optimising several conflicting goals; these types of problem are known as Multiobjective Optimisation Problems (MOPs). Evolutionary techniques have proved to be an effective tool for finding solutions to these MOPs during the last decade, Variations on the basic generic algorithm have been particulary proposed by different researchers for finding rapid optimal solutions to MOPs. The NSGA (Non-dominated Sorting Generic Algorithm) has been implemented in this paper for finding an optimal design for a shaft subjected to cyclic loads, the conflycting goals being minimum weight and minimum lateral deflection.

Optimising a shaft's geometry by applying genetic algorithms

María Alejandra Guzmán / Alberto Delgado

Many engnieering design tasks involve optimising several conflicting goals; these types of problem are known as Multiobjective Optimisation Problems (MOPs). Evolutionary techniques have proved to be an effective tool for finding solutions to these MOPs during the last decade, Variations on the basic generic algorithm have been particulary proposed by different researchers for finding rapid optimal solutions to MOPs. The NSGA (Non-dominated Sorting Generic Algorithm) has been implemented in this paper for finding an optimal design for a shaft subjected to cyclic loads, the conflycting goals being minimum weight and minimum lateral deflection.

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Title:

Optimising a shaft's geometry by applying genetic algorithms

Contributors:

María Alejandra Guzmán (author) / Alberto Delgado (author)

Published in:

Ingeniería e Investigación, Vol 25, Iss 2, Pp 15-23 (2005)

Publication date:

2005

ISSN:

0120-5609 , 2248-8723

Type of media:

Article (Journal)

Type of material:

Electronic Resource

Language:

Unknown

Keywords:

multiobjective optimisation , generic algorithms , mechanical design , shafts , Engineering (General). Civil engineering (General) , TA1-2040

Metadata by DOAJ is licensed under CC BY-SA 1.0

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