Multi-objective optimisation of induction heating processes

Methods of the problem solution and examples based on benchmark model

authored by: 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.
Organisation(s): Institute of Electrothermic Process Engineering
External Organisation(s): University of Pavia
Samara State Technical University
University of Padova
Type: Article
Journal: International Journal of Microstructure and Materials Properties
Volume: 8
Pages: 357-372
No. of pages: 16
ISSN: 1741-8410
Publication date: 08.10.2013
Publication status: Published
Peer reviewed: Yes
ASJC Scopus subject areas: General Materials Science
Sustainable Development Goals: SDG 7 - Affordable and Clean Energy
Electronic version(s): https://doi.org/10.1504/IJMMP.2013.057072 (Access: Closed)