Research on Multi-objective Optimization Problem of Engineering Project in 3D Field Based on Improved Particle Swarm Optimization Algorithm

2020 ◽  
pp. 35-43
Author(s):  
Jianqiang Zhao ◽  
Subei Li ◽  
Gefei Li
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Optimization Problem ◽  
Particle Swarm Optimization Algorithm ◽  
Particle Swarm ◽  
Multi Objective Optimization ◽  
Engineering Project ◽  
Swarm Optimization ◽  
Improved Particle Swarm Optimization ◽  
Multi Objective

Multi Objective Optimization of Cutting Process Based on Improved Particle Swarm Optimization Algorithm

2014 ◽  
Vol 800-801 ◽  
pp. 688-692
Author(s):  
Xue Liu ◽  
Cai Xu Yue ◽  
Ming Yang Wu ◽  
Yong Heng Yang ◽  
Guang Xu Ren ◽  
...  
Keyword(s):  
Particle Swarm Optimization ◽  
Cutting Force ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Cutting Temperature ◽  
Particle Swarm ◽  
Multi Objective Optimization ◽  
Swarm Optimization ◽  
Improved Particle Swarm Optimization ◽  
Multi Objective

With the rapid development of machinery industry, the processing parameters which affect on the quality of the products in machining and measuring index also appeared diversified, which makes the study of multi-objective optimization problem is very important. Among the many factors, cutting consumption plays a key role in many indicators, in effect, cutting force and cutting temperature on the quality and performance of products is the most prominent, so this paper takes PCBN tool cutting Cr12MoV steel as the experimental basis, the cutting parameters to optimize the parameters;the cutting force and cutting temperature as the index;with the aid of the BP neural network modeling of cutting force and cutting temperature, at the same time, this paper improved particle swarm optimization algorithm to achieve multiple objectives, provides multi objective optimization parameters more reliable for die steel production process.

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