Induction motor electromagnetic design optimization: Hooke Jeeves method versus genetic algorithms

2010 ◽  
Author(s):  
Lucian Tutelea ◽  
Ion Boldea
Keyword(s):  
Genetic Algorithms ◽  
Design Optimization ◽  
Induction Motor ◽  
Electromagnetic Design

scholarly journals A Parallel Surrogate Model Assisted Evolutionary Algorithm for Electromagnetic Design Optimization

2019 ◽  
Vol 3 (2) ◽  
pp. 93-105 ◽  
Author(s):  
Mobayode O. Akinsolu ◽  
Bo Liu ◽  
Vic Grout ◽  
Pavlos I. Lazaridis ◽  
Maria Evelina Mognaschi ◽  
...  
Keyword(s):  
Evolutionary Algorithm ◽  
Design Optimization ◽  
Surrogate Model ◽  
Electromagnetic Design

Design Optimization of a Special Class of Steel Structures via Genetic Algorithms and Stochastic Sampling

2009 ◽  
Author(s):  
Karim Hamza ◽  
Ashraf O. Nassef ◽  
Mohammed Shalaby
Keyword(s):  
Genetic Algorithms ◽  
Design Optimization ◽  
Special Class ◽  
Steel Structures ◽  
Sampling Technique ◽  
Manufacturing Cost ◽  
Stochastic Sampling ◽  
Optimization Task ◽  
Consistent Performance ◽  
Continuous And Discrete Variables

This paper addresses the design optimization of a special class of steel structures, which is clear-span building built up via off-shelf standard steel-sections. The problem is of particular importance in small to medium span buildings due to an attractive opportunity for reduction of the manufacturing cost compared to trusses and custom-built beams. The problem is also difficult from an optimization perspective as it exhibits both continuous and discrete variables, as well as discontinuities and flat regions in the topology of the objective function. Genetic algorithms (GA) and a special stochastic sampling technique are considered for the problem, as well as a mixed GA and stochastic sampling approach. The stochastic sampling is guided via heuristic rules based on knowledge specific to the problem, and is thus perceived well suited to the optimization task. While all the tested algorithms produced satisfactory results, the mixed approach seemed to yield the most consistent performance.

A rank-based constraint handling technique for engineering design optimization problems solved by genetic algorithms

2017 ◽  
Vol 187 ◽  
pp. 77-87 ◽  
Author(s):  
Rafael de Paula Garcia ◽  
Beatriz Souza Leite Pires de Lima ◽  
Afonso Celso de Castro Lemonge ◽  
Breno Pinheiro Jacob
Keyword(s):  
Genetic Algorithms ◽  
Design Optimization ◽  
Engineering Design ◽  
Optimization Problems ◽  
Constraint Handling ◽  
Engineering Design Optimization ◽  
Handling Technique
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