Inspired by the transmission of seeds in nature, an evolutionary algorithm, seed optimization algorithm (SOA), is proposed. The algorithm is designed by simulating the self-adaptive phenomena of plant and it can be used to resolve complex optimization problems with the evolution of plant. The global convergence analysis of SOA is made by using the Solis and Wets'research results. Finally, SOA is applied to three function optimization problems and compared with particle swarm optimization (PSO) algorithm. The experimental results show that SOA has stable and robust behaviour and it can be used as a promising alternative to existing optimization methods for engineering design.