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In this study, a continuous ant colony optimization algorithm on the basis of   probability density function was applied to the inverse problems of   one-dimensional coupled radiative and conductive heat transfer. To overcome   the slow convergence of the ant colony optimization algorithm for continuous   domain problems, a novel hybrid ant colony optimization and particle swarm   optimization algorithm was proposed. To illustrate the performances of these   algorithms, the thermal conductivity, absorption coefficient and scattering   coefficient of the one-dimensional homogeneous semi-transparent medium were   retrieved for several test cases. The temperature and radiative heat flux   simulated by the finite volume method were served as inputs for the inverse   analysis. Through function estimation and parameter estimation, the HAPO   algorithm was proved to be effective and robust

thermal science/thermal science

A novel hybrid ant colony optimization and particle swarm optimization algorithm for inverse problems of coupled radiative and conductive heat transfer