A Simple GA Based Approach for Multi-Objective Optimization of Machining Parameters

Abstract:

A simple approach to multi-objective optimization of machining parameters is presented. Regression analysis of experimental data is carried out to obtain the correlation between cutting parameters and response variables. Finally, Genetic Algorithm (GA) toolbox of MATLAB is used to carry out multi-objective optimization of two objective functions (surface roughness “Ra” & material removal rate “MRR”). Genetic algorithm is found to be a powerful tool for multi-objective optimization of machining parameters in this study.

• Periodical: Advanced Materials Research (Volume 974)
• Pages: 402-407
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.974.402
• Online since: June 2014
• Authors: Akhtar Waseem*, Jian Fei Su, Wu Yi Chen, Peng Fei Sun
• Keywords: Genetic Algorithm (GA), Machining Optimization, Multi-Objective Optimization (MOP), Regression Analysis

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