Multi-objective optimisation of induction heating processes

Methods of the problem solution and examples based on benchmark model

verfasst von: Paolo Di Barba, Yuliya Pleshivtseva, Edgar Rapoport, Michele Forzan, Sergio Lupi, Elisabetta Sieni, Bernard Nacke, Aleksandr Nikanorov
Abstract: The main goal of the researches is the development of new approaches, algorithms and numerical techniques for multi-objective optimisation of design of industrial induction heating installations. A multi-objective optimisation problem is mathematically formulated in terms of the typical optimisation criteria, e.g., maximum heating accuracy and minimum energy consumption. Various mathematical methods and algorithms for multi-objective optimisation, such as Non-dominated Sorting Genetic Algorithm (NSGA-II) and optimal control alternance method, have been implemented and integrated in a user-friendly automated optimal design package. Several optimisation procedures have been tested and investigated for a problem-oriented mathematical model in a number of comparative case studies. A general comparison of the design solutions based on NSGA-II and alternance method leads to their good agreement in all investigated cases. The methodology developed is planned to be applied to more complex real-life problems of the optimal design and control of different induction heating systems.
Organisationseinheit(en): Institut für Elektroprozesstechnik
Externe Organisation(en): Università degli Studi di Pavia
Samara State Technical University
Università degli Studi di Padova
Typ: Artikel
Journal: International Journal of Microstructure and Materials Properties
Band: 8
Seiten: 357-372
Anzahl der Seiten: 16
ISSN: 1741-8410
Publikationsdatum: 08.10.2013
Publikationsstatus: Veröffentlicht
Peer-reviewed: Ja
ASJC Scopus Sachgebiete: Allgemeine Materialwissenschaften
Ziele für nachhaltige Entwicklung: SDG 7 – Erschwingliche und saubere Energie
Elektronische Version(en): https://doi.org/10.1504/IJMMP.2013.057072 (Zugang: Geschlossen)

BibTeX

@article{b595264b2037499ca3d5f80de8d627ac,
title = "Multi-objective optimisation of induction heating processes: Methods of the problem solution and examples based on benchmark model",
abstract = "The main goal of the researches is the development of new approaches, algorithms and numerical techniques for multi-objective optimisation of design of industrial induction heating installations. A multi-objective optimisation problem is mathematically formulated in terms of the typical optimisation criteria, e.g., maximum heating accuracy and minimum energy consumption. Various mathematical methods and algorithms for multi-objective optimisation, such as Non-dominated Sorting Genetic Algorithm (NSGA-II) and optimal control alternance method, have been implemented and integrated in a user-friendly automated optimal design package. Several optimisation procedures have been tested and investigated for a problem-oriented mathematical model in a number of comparative case studies. A general comparison of the design solutions based on NSGA-II and alternance method leads to their good agreement in all investigated cases. The methodology developed is planned to be applied to more complex real-life problems of the optimal design and control of different induction heating systems.",
keywords = "Alternance method, Genetic algorithms, Induction heating installation, Multi-objective optimisation, NSGA-II, Optimal design, Pareto-optimality theory",
author = "{Di Barba}, Paolo and Yuliya Pleshivtseva and Edgar Rapoport and Michele Forzan and Sergio Lupi and Elisabetta Sieni and Bernard Nacke and Aleksandr Nikanorov",
year = "2013",
month = oct,
day = "8",
doi = "10.1504/IJMMP.2013.057072",
language = "English",
volume = "8",
pages = "357--372",
journal = "International Journal of Microstructure and Materials Properties",
issn = "1741-8410",
publisher = "Inderscience Enterprises Ltd.",
number = "4-5",
}