@ARTICLE{10.21494/ISTE.OP.2022.0779, 

TITLE={Optimization of the cost of industrial packaging by PSO, SA and GA optimization algorithms}, 
  
AUTHOR={Sara Rhouas, Norelislam El Hami, }, 
	
JOURNAL={Uncertainties and Reliability of Multiphysical Systems}, 
	
VOLUME={5}, 

NUMBER={Issue 1}, 
	
YEAR={2022}, 

URL={http://openscience.fr/Optimization-of-the-cost-of-industrial-packaging-by-PSO-SA-and-GA-optimization}, 
	
DOI={10.21494/ISTE.OP.2022.0779}, 
	
ISSN={2514-569X}, 
	
ABSTRACT={The metaheuristic known as the optimization algorithm; a resolution of difficult problems of minimization or maximization of a function in order to find almost optimal solutions. There are a wide variety of metaheuristics, but in this research article we will only talk about three optimization algorithms that will help us optimize the cost of packaging an industry by using MATLAB software to program them. The first algorithm is the best-known particle swarm optimization in the optimization field, which is inspired by the simulation movement of a group of birds, the second is the simulated annealing inspired by annealing in metallurgy, a Heat treatment technique also involving controlled cooling of a material which affects both temperature and energy. And the last is the genetic algorithm which is commonly used to give high quality results to optimization problems by relying on bio-inspired operators such as mutation, crossing and selection. We will compare the performance of each of them using the test functions according to their uptime and convergence and will apply to our industrial optimization problem.}}