Abstract: Research about heat conduction inverse problem be late in domestic, there are lot of the research technique, but ordinary methods are hard to be at the holistic best point. our purpose is to study the application of Quantum-Behaved Partical Swarm Optimization(QPSO) in the two-dimensional heat conduction on the ground of classical Particle Swarm Optimizatio(PSO).And introduce how to use the above algorithm based on the objective function to seek the best parameter combination. In order to enhance the algorithm the astringency and the stability we make the improvement to the algorithm, and has carried on the massive experiments. The result shows in the solution heat conduction inverse problem optimization question, based on QPSO algorithm works well on heat conduction inverse problem , and prove QPSO had deteminate practical application value in the heat conduction domain.