Parallel Gene Expression Programming Based on EDA

In order to reduce the computation time and improve the quality of solutions of Gene Expression Programming (GEP),synchronous and asynchronous distributed parallel GEP algorithm based on Estimation of Distribution Algorithm (EDA) was proposed.The idea of introducing EDA into GEP is to accelerate the convergence speed.Moreover, the improved GEP was implemented by synchronous and asynchronous distributed parallel method based on the island parallel model.Some experiments were done on distributed network connected by twenty computers.The best results of sequential and parallel algorithms were compared,speedup and performance influence of some important parallel control parameters to this parallel algorithm were discussed.The experimental results show that parallel algorithms may approach linear speedup and have better ability to find optimal solution and higher stability than sequential algorithm.