Abstract
In general, a genetic algorithm combined with other algorithms (e.g. tabu search, simulated annealing, etc.) is well known to be a powerful approach. In this paper, an efficient hybrid approach containing local search and genetic algorithms is presented. The purpose of the using local search mechanisms is to provide better the solution quality and to increase the convergence speed. It is demonstrated that the performance of the proposed algorithms is significantly better than the conventional genetic algorithm methods.
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Mutluer, M., Bilgin, O., Çunkaş, M. (2007). Parameter Determination of Induction Machines by Hybrid Genetic Algorithms. In: Apolloni, B., Howlett, R.J., Jain, L. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2007. Lecture Notes in Computer Science(), vol 4692. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74819-9_15
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DOI: https://doi.org/10.1007/978-3-540-74819-9_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74817-5
Online ISBN: 978-3-540-74819-9
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