Přejít k obsahu


Genetic algorithms for multicriteria shape optimization of induction furnace

Citace: KŮS, P., MACH, F., KARBAN, P., DOLEŽEL, I. Genetic algorithms for multicriteria shape optimization of induction furnace. In AIP Conference Proceedings. Melville: American Institute of Physics Inc., 2012. s. 2344-2347. ISBN: 978-0-7354-1091-6 , ISSN: 0094-243X
Druh: STAŤ VE SBORNÍKU
Jazyk publikace: eng
Anglický název: Genetic algorithms for multicriteria shape optimization of induction furnace
Rok vydání: 2012
Místo konání: Melville
Název zdroje: American Institute of Physics Inc.
Autoři: RNDr. Pavel Kůs Ph.D. , Ing. František Mach , Doc. Ing. Pavel Karban Ph.D. , Prof. Ing. Ivo Doležel CSc.
Abstrakt EN: In this contribution we deal with a multi-criteria shape optimization of an induction furnace. We want to find shape parameters of the furnace in such a way, that two different criteria are optimized. Since they cannot be optimized simultaneously, instead of one optimum we find set of partially optimal designs, so called Pareto front. We compare two different approaches to the optimization, one using nonlinear conjugate gradient method and second using variation of genetic algorithm. As can be seen from the numerical results, genetic algorithm seems to be the right choice for this problem. Solution of direct problem (coupled problem consisting of magnetic and heat field) is done using our own code Agros2D. It uses finite elements of higher order leading to fast and accurate solution of relatively complicated coupled problem. It also provides advanced scripting support, allowing us to prepare parametric model of the furnace and simply incorporate various types of optimization algorithms. ? 2012 American Institute of Physics.
Klíčová slova

Zpět

Patička