Title: Real valued genetic algorithm for solving an inverse hyperbolic problem: multi-core parallelisation approach

Authors: Reza Pourgholi; Amin Esfahani; Hassan Dana

Addresses: School of Mathematics and Computer Sciences, Damghan University, Damghan 36715-364, Iran ' School of Mathematics and Computer Sciences, Damghan University, Damghan 36715-364, Iran ' School of Mathematics and Computer Sciences, Damghan University, Damghan 36715-364, Iran

Abstract: In this paper, a numerical approach combining the use of the least squares method and the genetic algorithm (sequential and multi-core parallelisation approach) is proposed for the determination of temperature in an inverse hyperbolic heat conduction problem (IHHCP). Some numerical experiments confirm the utility of this algorithm as the results are in good agreement with the exact data. Results show that an excellent estimation can be obtained by implementation sequential genetic algorithm within a CPU with clock speed 2.4 GHz, and parallel genetic algorithm within a 16-core CPU with clock speed 2.4 GHz for each core.

Keywords: inverse hyperbolic heat conduction problem; IHHCP; inverse hyperbolic heat; genetic algorithms; multi-core parallelisation; least squares method.

DOI: 10.1504/IJMMNO.2013.059206

International Journal of Mathematical Modelling and Numerical Optimisation, 2013 Vol.4 No.4, pp.410 - 424

Available online: 07 Feb 2014 *

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