Comparison of NSGA-II, MOALO and MODA for Multi-Objective Optimization of Micro-Machining Processes

Materials

Milan Joshi¹  S. Madhu²  Ranjan Kumar Ghadai³  Kanak Kalita⁴  Xiao-Zhi Gao⁵ 

[1] Department of Applied Science and Humanities, MPSTME SVKM’S Narsee Monjee Institute of Management Studies, Shirpur 425 405, India;Department of Automobile Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai 602 105, India;Department of Mechanical Engineering, Sikkim Manipal Institute of Technology, Sikkim Manipal University, Majhitar 737 136, India;Department of Mechanical Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Avadi 600 062, India;School of Computing, University of Eastern Finland, FI-70210 Kuopio, Finland;

关键词: process optimization;    metaheuristics;    ant lion optimization;    dragonfly algorithm;    NSGA;   

DOI  :  10.3390/ma14175109

来源: DOAJ

【 摘 要 】

The popularity of micro-machining is rapidly increasing due to the growing demands for miniature products. Among different micro-machining approaches, micro-turning and micro-milling are widely used in the manufacturing industry. The various cutting parameters of micro-turning and micro-milling has a significant effect on the machining performance. Thus, it is essential that the cutting parameters are optimized to obtain the most from the machining process. However, it is often seen that many machining objectives have conflicting parameter settings. For example, generally, a high material removal rate (MRR) is accompanied by high surface roughness (SR). In this paper, metaheuristic multi-objective optimization algorithms are utilized to generate Pareto optimal solutions for micro-turning and micro-milling applications. A comparative study is carried out to assess the performance of non-dominated sorting genetic algorithm II (NSGA-II), multi-objective ant lion optimization (MOALO) and multi-objective dragonfly optimization (MODA) in micro-machining applications. The complex proportional assessment (COPRAS) method is used to compare the NSGA-II, MOALO and MODA generated Pareto solutions.

【 授权许可】

Unknown