Multi-objective Optimization in Geometric Design of Active Magnetic Bearing based on Force Slew Rate, Overall Volume, and Total Losses Considerations through Genetic Algorithms

2021 ◽  
Author(s):  
Vinay Kumar Yadav ◽  
Punit Kumar ◽  
Gian Bhushan
Keyword(s):  
Genetic Algorithms ◽  
Magnetic Bearing ◽  
Geometric Design ◽  
Active Magnetic Bearing ◽  
Slew Rate ◽  
Multi Objective Optimization ◽  
Multi Objective

How Genetic Algorithms Handle Pareto-Optimality in Design and Manufacturing

2007 ◽  
pp. 465-482
Author(s):  
N. Chakraborti
Keyword(s):  
Genetic Algorithms ◽  
Evolutionary Algorithms ◽  
Pareto Optimality ◽  
Multi Objective Optimization ◽  
Recent Past ◽  
Multi Objective ◽  
Manufacturing Sectors ◽  
Design And Manufacturing ◽  
Basic Concepts

An informal analysis is provided for the basic concepts associated with multi-objective optimization and the notion of Pareto-optimality, particularly in the context of genetic algorithms. A number of evolutionary algorithms developed for this purpose are also briefly introduced, and finally, a number of paradigm examples are presented from the materials and manufacturing sectors, where multi-objective genetic algorithms have been successfully utilized in the recent past.

Sign in / Sign up

Export Citation Format

Share Document