Multi-objective optimisation of induction heating processes: methods of the problem solution and examples based on benchmark model
by Paolo Di Barba; Yuliya Pleshivtseva; Edgar Rapoport; Michele Forzan; Sergio Lupi; Elisabetta Sieni; Bernard Nacke; Aleksandr Nikanorov
International Journal of Microstructure and Materials Properties (IJMMP), Vol. 8, No. 4/5, 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.

Online publication date: Mon, 07-Oct-2013

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