Resumen

GUZMAN, María Alejandra  y  DELGADO, Alberto. Optimising a shaft’s geometry by applying genetic algorithms. Ing. Investig. [online]. 2005, vol.25, n.2, pp.15-23. ISSN 0120-5609.

Many engineering 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 genetic algorithm have been particularly proposed by different researchers for finding rapid optimal solutions to MOPs. The NSGA (non-dominated sorting genetic algorithm) has been implemented in this paper for finding an optimal design for a shaft subjected to cyclic loads, the conflicting goals being minimum weight and minimum lateral deflection.

Palabras clave : multiobjective optimisation; genetic algorithms; mechanical design; shafts.

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