Efficient GA Approach Combined with Taguchi Method for Mixed Constrained Circuit Design

Hybrid Taguchi DNA Swarm Intelligence for Optimal Inverse Kinematics Redundancy Resolution of Six-DOF Humanoid Robot Arms

“…This approach not only greatly reduces the number of iterations but also makes the DNA final solution approaches the optimal values with less randomness. Taguchi method was constructed based on the principle of an orthogonal array that can effectively minimize the number of experiments required in any design process [21][22][23][24][25]. An orthogonal array is a fractional factorial matrix that provides a balanced comparison of levels of parameters or factors.…”

“…Signal-to-noise ratio (SNR) is used in Taguchi method to measure the quality of each experiment in the orthogonal array. There are several SNRs available depending on the type of characteristic: nominal-is-best, smaller-the-better, or larger-the-better [21][22][23][24][25]. This paper adopts the smaller-thebetter characteristic and the SNR is given by SNR = −10 log 2 ,…”

“…Taguchi method is a statistical method developed by Genichi Taguchi to improve the product quality and cost in industrial design [21][22][23][24][25]. This approach has proven to be an important tool in the system design and process quality in which the best setting of the control factors (parameters) is determined and has been applied to solve many optimization problems in electrical machines design, aerospace engineering, and controller design.…”

“…This approach has proven to be an important tool in the system design and process quality in which the best setting of the control factors (parameters) is determined and has been applied to solve many optimization problems in electrical machines design, aerospace engineering, and controller design. For example, Su et al [22] proposed an efficient GA approach combined with Taguchi method for mixed constrained circuit design. Yang et al [23] employed the Taguchi method combined with GA to design a flight controller.…”

A Robust Intelligent Framework for Multiple Response Statistical Optimization Problems Based on Artificial Neural Network and Taguchi Method

“…In this regard, Ko et al [4] employed Taguchi method and artificial neural network to perform design in multistage metal forming processes considering work ability limited by ductile fracture. Su et al [5] proposed a new circuit design optimization method where genetic algorithm (GA) is combined with Taguchi method. Lo and Tsao [6] modified an analytical linkage-spring model based on neural network analysis and the Taguchi method to determine the design rules for reducing the loop height and the sagging altitude of gold wire-bonding process of the integrated circuit (IC) package.…”