Optimal Topology Design of Products Using Genetic Algorithm

2004 ◽  
Author(s):  
N. Swaminathan
Keyword(s):  
Genetic Algorithm ◽  
Topology Design ◽  
Optimal Topology

Synthesis of Compliant Mechanisms for Path Generation using Genetic Algorithm

2004 ◽  
Vol 127 (4) ◽  
pp. 745-752 ◽  
Author(s):  
Anupam Saxena
Keyword(s):  
Genetic Algorithm ◽  
Nonlinear Analysis ◽  
Compliant Mechanisms ◽  
Topology Design ◽  
Optimal Topology ◽  
Path Generation ◽  
Geometrically Nonlinear Analysis ◽  
Design Variables ◽  
Gradient Based ◽  
Shape And Size

In this paper is described a procedure to synthesize the optimal topology, shape, and size of compliant continua for a given nonlinear output path. The path is prescribed using a finite number of distinct precision points much in accordance with the synthesis for path generation in traditional kinematics. Geometrically nonlinear analysis is employed to model large displacements of the constituent members. It is also essential to employ nonlinear analysis to allow the output port to negotiate the prescribed path accurately. The topology synthesis problem is addressed in its original binary form in that the corresponding design variables are only allowed to assume values of “0” for no material and “1” for the material present at a site in the design region. Shape and size design variables are modeled using continuous functions. Owing to the discrete nature of topology design variables, since gradient based optimization methods cannot be employed, a genetic algorithm is used that utilizes only the objective values to approach an optimum solution. A notable advantage of a genetic algorithm over its gradient based counterparts is the implicit circumvention of nonconvergence in the large displacement analysis, which is another reason why a genetic algorithm is chosen for optimization. The least squared objective is used to compare the design and desired output responses. To allow a user to specify preference for a precision point, individual multiple least squared objectives, same in number as the precision points are used. The multiple objectives are solved using Nondominated Sorting in Genetic Algorithm (NSGA-II) to yield a set of pareto optimal solutions. Thus, multiple solutions for compliant mechanisms can be obtained such that a mechanism can traverse one or some precision points among those specified more precisely. To traverse the entire path, a solution that minimizes the sum of individual least square objectives may be chosen. Synthesis examples are presented to demonstrate the usefulness of the proposed method that is capable of generating a solution that can be manufactured as is without requiring any interpretation.

Optimal topology for consensus using genetic algorithm

2020 ◽  
Vol 404 ◽  
pp. 41-49
Author(s):  
Sabyasachi Mondal ◽  
Antonios Tsourdos
Keyword(s):  
Genetic Algorithm ◽  
Optimal Topology

scholarly journals Genetic Algorithm for Holistic VNF-Mapping and Virtual Topology Design

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 55893-55904 ◽  
Author(s):  
Lidia Ruiz ◽  
Ramon J. Duran Barroso ◽  
Ignacio De Miguel ◽  
Noemi Merayo ◽  
Juan Carlos Aguado ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Topology Design ◽  
Virtual Topology

Optimal topology design using a global self-organisational approach

1998 ◽  
Vol 35 (3-4) ◽  
pp. 219-237 ◽  
Author(s):  
W.M. Payten ◽  
B. Ben-Nissan ◽  
D.J. Mercert
Keyword(s):  
Topology Design ◽  
Optimal Topology

Optimal Topology Design of Complex Networks

2009 ◽  
Author(s):  
Fernanda S. H. Souza ◽  
Alexandre Salles da Cunha ◽  
Geraldo Robson Mateus
Keyword(s):  
Complex Networks ◽  
Topology Design ◽  
Optimal Topology
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