Optimization with Genetic Algorithms and Splines as a way for Computer Aided Innovation

Abstract

This paper describes the conceptual foundations to construct a method on Computer 
Aided Innovation for product development. It begins with a brief recap of the different 
methodologies and disciplines that build its bases. Evolutionary Design is presented and 
explained how the First activities in Genetic Algorithms (GAs) helped to produce computer 
shapes that resembled a creative behavior. A description of optimization processes based 
on Genetic Algorithms is presented, and some of the genetic operators are explained as a 
background of the creative operators that are intended to be developed. A summary of some 
Design Optimization Systems is also explained and its use of splined profiles to optimize 
mechanical structures. The approach to niulti-objective optimization with Genetic Algorithms 
is analyzed from the point of view of Pareto diagrams. It is discussed how the transition from 
a multi-objective optimization conflict to a solution with the aim of an ideal result can be developed 
means the help of TRIZ (Theory of Inventive Problem Solving), complementing the discipline 
of Evolutionary Design. Similarities between Genetic Algorithms and TRIZ regarding ideality 
and evolution are identified and presented. Finally, a brief presentation of a case study about 
the design of engine crankshafts is used to explain the concepts and methods deployed. The 
authors have been working on strategies to optimize the balance of a crankshaft using CAD 
and CAE software, splines, Genetic Algorithms, and tools for its integration [1] [2].