To solve the inverse heat conduction problem with unknown location of heat source,an ant colony algorithm with dynamic parameters,being a probabilistic algorithm,was proposed.The analysis and calculation show that the pheromone inspiration factor,visibility inspiration factor,pheromone evaporation rate and other ant colony parameters directly impact the way of updating the pheromone concentrations.Their values ultimately affect the accuracy of the results and the convergence rate.In the calculation process,the pheromone concentrations on the path will be constantly changing,and the ants will tend to select a concentrated path.The ant colony optimization algorithm with constant ant colony parameter values can't guarantee to have good performance in the entire calculation process.Therefore,the ant colony algorithm with dynamic parameters was proposed,and the dynamic function of ant colony parameter values which changes with the times of global cycles was constructed according to the calculation results of the analysis.The results show that the proposed method is an accurate and efficient method to seek the location of heat source in inverse heat conduction problems.