Parallel genetic algorithms for the solution of inverse heat conduction problems

Abstract

A parallel genetic algorithm (PGA) is proposed for the solution of two-dimensional inverse heat conduction problems involving unknown thermophysical material properties. Experimental results show that the proposed PGA is a feasible and effective optimization tool for inverse heat conduction problems.

Keywords:

• Heat conduction
• Inverse problem
• Parallel genetic algorithm

Acknowledgements

This project was supported by the Natural Science Foundation of China (NSFC Grant 60173046). Part of this research was conducted during visits of the first and third authors to the University of Greenwich supported by UK EPSRC Grant GR/T10183/01.