Details
| Original language | English |
|---|---|
| Pages (from-to) | 357-372 |
| Number of pages | 16 |
| Journal | International Journal of Microstructure and Materials Properties |
| Volume | 8 |
| Issue number | 4-5 |
| Publication status | Published - 8 Oct 2013 |
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
ASJC Scopus subject areas
- Materials Science(all)
- General Materials Science
Sustainable Development Goals
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In: International Journal of Microstructure and Materials Properties, Vol. 8, No. 4-5, 08.10.2013, p. 357-372.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Multi-objective optimisation of induction heating processes
T2 - Methods of the problem solution and examples based on benchmark model
AU - Di Barba, Paolo
AU - Pleshivtseva, Yuliya
AU - Rapoport, Edgar
AU - Forzan, Michele
AU - Lupi, Sergio
AU - Sieni, Elisabetta
AU - Nacke, Bernard
AU - Nikanorov, Aleksandr
PY - 2013/10/8
Y1 - 2013/10/8
N2 - 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.
AB - 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.
KW - Alternance method
KW - Genetic algorithms
KW - Induction heating installation
KW - Multi-objective optimisation
KW - NSGA-II
KW - Optimal design
KW - Pareto-optimality theory
UR - http://www.scopus.com/inward/record.url?scp=84885399319&partnerID=8YFLogxK
U2 - 10.1504/IJMMP.2013.057072
DO - 10.1504/IJMMP.2013.057072
M3 - Article
AN - SCOPUS:84885399319
VL - 8
SP - 357
EP - 372
JO - International Journal of Microstructure and Materials Properties
JF - International Journal of Microstructure and Materials Properties
SN - 1741-8410
IS - 4-5
ER -