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

被引：29

作者：

Joshi, Milan ^{[1
]}

Ghadai, Ranjan Kumar ^{[2
]}

Madhu, S. ^{[3
]}

Kalita, Kanak ^{[4
]}

Gao, Xiao-Zhi ^{[5
]}

机构：

[1] MPSTME SVKMS Narsee Monjee Inst Management Studie, Dept Appl Sci & Humanities, Shirpur 425405, India

[2] Sikkim Manipal Univ, Sikkim Manipal Inst Technol, Dept Mech Engn, Majhitar 737136, India

[3] Saveetha Inst Med & Tech Sci, Saveetha Sch Engn, Dept Automobile Engn, Chennai 602105, Tamil Nadu, India

[4] Vel Tech Rangarajan Dr Sagunthala R&D Inst Sci &, Dept Mech Engn, Avadi 600062, India

[5] Univ Eastern Finland, Sch Comp, FI-70210 Kuopio, Finland

来源：

MATERIALS | 2021年 / 14卷 / 17期

关键词：

process optimization; metaheuristics; ant lion optimization; dragonfly algorithm; NSGA; PROCESS PARAMETER OPTIMIZATION; RESPONSE-SURFACE METHODOLOGY; TURNING PROCESS; GENETIC ALGORITHM; ROUGHNESS; EDM;

D O I：

10.3390/ma14175109

中图分类号：

O64 [物理化学（理论化学）、化学物理学];

学科分类号：

070304 ; 081704 ;

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.

引用

页数：15

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