Dynamic model of multi-agent social evolutionary algorithm and its convergence

With a typical and simple 2-bit problem, a dynamic model of multi-agent social evolutionary algorithm (MASEA) is constructed by dynamic method. Then, the global dynamic shape of MASEA is comprehensively analyzed and the common evolution operators are also formally described. Furthermore, the effect that every evolutionary operator has on the dynamic shape is discovered by attraction analysis of the fixed points in the models. The global convergence of MASEA is also proved.