Supply chain optimization is an important and difficult problem in supply chain management. Firstly, a novel supply chain optimization model was proposed in the paper. Secondly, the generalized Genetic Algorithm (GA) that embedded particular natural evaluative rules was built, and Generalized Genetic Particle Swarm Optimization (GGPSO) was gotten by combining GA and PSO. The novel method overcomes the local convergence of PSO and improves its global research ability. The experimental results show that GGPSO does better than branch and bound methods, traditional GA and PSO.