Authors :
Tchikdje K. Marthe P. ; Kalameu Alain; Djeumako Bonaventure; Kenmeugne Bienvenu; Annouar Djidda Mahamat
Volume/Issue :
Volume 8 - 2023, Issue 12 - December
Google Scholar :
http://tinyurl.com/5c2r2ujc
Scribd :
http://tinyurl.com/fza9jy84
DOI :
https://doi.org/10.5281/zenodo.10488254
Abstract :
This paper presents new Particle Swarm
Optimization algorithm for the determination of
Chaboche model parameter. This is based on the
reduction of search-space where the optimal
parametersare belonged. The obtained results are
compared to other metaheuristic approaches mainly the
Genetic Algorithm and standard Particle Swarm
Optimization by using the Mean Square Error and
optimization time as criteria.The first yielded0.316 for
a new approach. Despite this efficiency, the proposed
approach has the highest optimization time, which is
787 seconds against 712 seconds for a standard Particle
Swarm Optimization, and 615seconds for a Genetic
Algorithm.
Keywords :
Chaboche model; hardening parameter;genetic algorithm and particle swarm optimization.
This paper presents new Particle Swarm
Optimization algorithm for the determination of
Chaboche model parameter. This is based on the
reduction of search-space where the optimal
parametersare belonged. The obtained results are
compared to other metaheuristic approaches mainly the
Genetic Algorithm and standard Particle Swarm
Optimization by using the Mean Square Error and
optimization time as criteria.The first yielded0.316 for
a new approach. Despite this efficiency, the proposed
approach has the highest optimization time, which is
787 seconds against 712 seconds for a standard Particle
Swarm Optimization, and 615seconds for a Genetic
Algorithm.
Keywords :
Chaboche model; hardening parameter;genetic algorithm and particle swarm optimization.
