Genetic Algorithm Parameter Optimization using Taguchi Robust Design for Multi-response Optimization of Experimental and Historical Data

Majumdar, Angshuman; Ghosh, Debashis

doi:10.5120/ijca2015906383

Cited by 8 publications

(4 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The Taguchi orthogonal experimental design is a method for independently evaluating the single-factor-level effects [ 55 ]. Eighteen compounds were chosen as external additives in this study.…”

Section: Methodsmentioning

confidence: 99%

Triazine Herbicides Risk Management Strategies on Environmental and Human Health Aspects Using In-Silico Methods

Yao

Sun

Zhao

2023

IJMS

View full text Add to dashboard Cite

As an effective herbicide, 1, 3, 5-Triazine herbicides (S-THs) are used widely in the pesticide market. However, due to their chemical properties, S-THs severely threaten the environment and human health (e.g., human lung cytotoxicity). In this study, molecular docking, Analytic Hierarchy Process—Technique for Order Preference by Similarity to the Ideal Solution (AHP-TOPSIS), and a three-dimensional quantitative structure-active relationship (3D-QSAR) model were used to design S-TH substitutes with high herbicidal functionality, high microbial degradability, and low human lung cytotoxicity. We discovered a substitute, Derivative-5, with excellent overall performance. Furthermore, Taguchi orthogonal experiments, full factorial design of experiments, and the molecular dynamics method were used to identify three chemicals (namely, the coexistence of aspartic acid, alanine, and glycine) that could promote the degradation of S-THs in maize cropping fields. Finally, density functional theory (DFT), Estimation Programs Interface (EPI), pharmacokinetic, and toxicokinetic methods were used to further verify the high microbial degradability, favorable aquatic environment, and human health friendliness of Derivative 5. This study provided a new direction for further optimizations of novel pesticide chemicals.

show abstract

Section: Methodsmentioning

confidence: 99%

Triazine Herbicides Risk Management Strategies on Environmental and Human Health Aspects Using In-Silico Methods

Yao

Sun

Zhao

2023

IJMS

View full text Add to dashboard Cite

show abstract

“…Taguchi Method is used for statistical analysis of the problem. Taguchi OA is the best tool to work with when there is a large number of parameters [1] .Taguchi OA is a factorial design matrix that is highly fractional in nature proposed by Dr. Genichi Taguchi. It is a balanced design to ensure that all levels of every factor are equally considered.…”

Section: B Taguchi Methodsmentioning

confidence: 99%

Parameter Tuning Method for Genetic Algorithm using Taguchi Orthogonal Array for Non-linear Multimodal Optimization Problem

Naruka¹,

Yadav²,

Sharma³

et al. 2019

IJRTE

View full text Add to dashboard Cite

Genetic algorithm (GA) is the most widely used meta-heuristic optimization algorithm that can solve complex large scale optimization problems successfully. The only problem lies with the setting of GA control parameters and their levels for the optimal performance of the algorithm. The statistical method can be used for parameter tuning that allows us to collect data properly. Also, it analyzes the collected data accurately and presents the appropriate results. For statistical analysis, Taguchi's robust factorial design which is highly fractional in nature with a special set of L32 orthogonal array (OA) is used. Taguchi's robust design is a proficient method to find an optimum solution with a minimal number of designs of experiment (DOE). Analysis of variance (ANOVA) is conducted to check whether GA control parameters are statistically significant or not for non-linear multimodal optimization problems. Taguchi OA design and ANOVA analysis experimental study is conducted using Stat-Ease software and for the Genetic Algorithm control parameter setting GA solver of MATLAB is used.

show abstract

“…However, GAs have limitations regarding the optimality of individuals which satisfy the given fitness function unless an appropriate input parameter is selected. Consequently, to overcome this drawback, a different scheme has been utilized for tuning a suitable parameter for a genetic algorithm [41][42][43]. Among various techniques, the Taguchi experimental design approach is used for tuning the parameters of the GA solver.…”

Section: Taguchi Experimental Designmentioning

confidence: 99%

Beam Deflection Monitoring Based on a Genetic Algorithm Using Lidar Data

Maru

Lee

Cha

et al. 2020

Sensors

View full text Add to dashboard Cite

The Light Detection And Ranging (LiDAR) system has become a prominent tool in structural health monitoring. Among such systems, Terrestrial Laser Scanning (TLS) is a potential technology for the acquisition of three-dimensional (3D) information to assess structural health conditions. This paper enhances the application of TLS to damage detection and shape change analysis for structural element specimens. Specifically, estimating the deflection of a structural element with the aid of a Lidar system is introduced in this study. The proposed approach was validated by an indoor experiment by inducing artificial deflection on a simply supported beam. A robust genetic algorithm method is utilized to enhance the accuracy level of measuring deflection using lidar data. The proposed research primarily covers robust optimization of a genetic algorithm control parameter using the Taguchi experiment design. Once the acquired data is defined in terms of plane, which has minimum error, using a genetic algorithm and the deflection of the specimen can be extracted from the shape change analysis.

show abstract

Genetic Algorithm Parameter Optimization using Taguchi Robust Design for Multi-response Optimization of Experimental and Historical Data

Cited by 8 publications

References 8 publications

Triazine Herbicides Risk Management Strategies on Environmental and Human Health Aspects Using In-Silico Methods

Triazine Herbicides Risk Management Strategies on Environmental and Human Health Aspects Using In-Silico Methods

Parameter Tuning Method for Genetic Algorithm using Taguchi Orthogonal Array for Non-linear Multimodal Optimization Problem

Beam Deflection Monitoring Based on a Genetic Algorithm Using Lidar Data

Contact Info

Product

Resources

About