Compare various Circuits Area Reduction using Genetic Algorithm and Hybrid Partitioning Algorithm

This paper describes a new method for design optimization of process variables in multi-pass wire drawing processes. An adaptive Micro Genetic Algorithm (μGA) has been implemented for minimizing the difference between maximum and minimum effective plastic strains in the end product and also for minimizing the total deformation energy in a multi-pass wire drawing process. The chosen design variables are die angles, area reduction ratios, and the total number of passes. Significant improvements in the simulated product quality and reduction in the number of passes have been observed as a result of the Genetic Algorithm based optimization process. The choice of annealing passes for further reduction of the total deformation energy and residual stresses has also been studied.

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A genetic algorithm based partition generation and optimization method for finite element problems

10.32920/ryerson.14652276.v1 ◽

2021 ◽

Author(s):

Lubomir Jirasek

Keyword(s):

Genetic Algorithm ◽

Load Balance ◽

Optimization Problem ◽

Direct Method ◽

Optimization Method ◽

Time Savings ◽

Partitioning Algorithm ◽

A Direct Method ◽

Single Processor ◽

Compute Time

A two-step partitioning algorithm for FE meshes is proposed in this work for the purposes of time savings. A direct method based on the concept of 'separateness' was applied first, followed by a partition optimization process that used a Genetic Algorithm (GA). A total of 9 applications were evaluated to demonstrate the durability, versatility, and effectiveness of this partitioning algorithm with respect to interface node count and subdomain load balance. Beyond this wingbox optimization problem was performed on a single processor using a GA to demonstrate the possible time savings of the method. With a 30% decrease in compute time witnessed, it can be said with confidence that the propose partitioning algorithm was a success.

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Hardware/Software Partitioning Algorithm Based on Genetic Algorithm

Journal of Computers ◽

10.4304/jcp.9.6.1309-1315 ◽

2014 ◽

Vol 9 (6) ◽

Cited By ~ 6

Author(s):

Shuai Guo Li ◽

Fu Jin Feng ◽

Hua Jun Hu ◽

Cong Wang ◽

Duo Qi

Keyword(s):

Genetic Algorithm ◽

Partitioning Algorithm ◽

Software Partitioning

Download Full-text

A genetic algorithm based partition generation and optimization method for finite element problems

10.32920/ryerson.14652276 ◽

2021 ◽

Author(s):

Lubomir Jirasek

Keyword(s):

Genetic Algorithm ◽

Load Balance ◽

Optimization Problem ◽

Direct Method ◽

Optimization Method ◽

Time Savings ◽

Partitioning Algorithm ◽

A Direct Method ◽

Single Processor ◽

Compute Time

A two-step partitioning algorithm for FE meshes is proposed in this work for the purposes of time savings. A direct method based on the concept of 'separateness' was applied first, followed by a partition optimization process that used a Genetic Algorithm (GA). A total of 9 applications were evaluated to demonstrate the durability, versatility, and effectiveness of this partitioning algorithm with respect to interface node count and subdomain load balance. Beyond this wingbox optimization problem was performed on a single processor using a GA to demonstrate the possible time savings of the method. With a 30% decrease in compute time witnessed, it can be said with confidence that the propose partitioning algorithm was a success.

Download Full-text