Optimization of parameters in die casting and compression processes using the particle swarm algorithm

In this article, an algorithm, based on the particle swarm technique (PSO), is developed to optimize die casting and compression casting processes, using mathematical models to describe the behavior of both processes. In compression casting the mathematical model describes a problem with multiple ob...

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Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας: González-Rondón, Yordy (author)
Άλλοι συγγραφείς: Rengel, José Eduardo (author), Martínez, Johnny J. (author)
Μορφή: article
Γλώσσα:Ισπανικά
Έκδοση: 2021
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Διαθέσιμο Online:http://revistas.um.edu.uy/index.php/ingenieria/article/view/852
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Περιγραφή
Περίληψη:In this article, an algorithm, based on the particle swarm technique (PSO), is developed to optimize die casting and compression casting processes, using mathematical models to describe the behavior of both processes. In compression casting the mathematical model describes a problem with multiple objectives and constraints, and in die casting the model describes a single objective problem with constraints. The development of the PSO algorithm was carried out with the FORTRAN 90 software, and the results were compared with those reported by a teaching-learning based optimization algorithm, (TLBO), demonstrating good capabilities in the optimization of parameters in die casting and by compression. It was observed that the PSO algorithm achieves an optimal solution in all processes and the computational time were minimal.