Solving an inverse heat conduction problem using genetic algorithm: Sequential and multi-core parallelization approach

In this paper a numerical approach combining the least squares method and the genetic algorithm (sequential and multi-core parallelization approach) is proposed for the determination of temperature in an inverse heat conduction problem (IHCP). 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 2.7GHz, and parallel genetic algorithm within a 16-core CPU with clock speed 2.7GHz for each core.