A genetic algorithm for combined parameter and tolerance design optimization

Many research papers have been tried to optimize the parameter and tolerance designs. Parameter and tolerance design are the main key to achieve high quality of products. However, high cost still remain in the process due to reducing the tolerance limit. The objective of this work is combines the optimization of parameter and tolerance design in one stage in to the cost function. This cost function is the sum of tolerance cost function and quality loss function. Taylor expansion will be applied in the genetic algorithm, is considering close attention regarding its potential as a novel optimization technique for searching the optimization value.