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The material distribution routing problem in the manufacturing system is a complex combinatorial optimization problem and its main task is to deliver materials to the working stations with low cost and high efficiency.A multi-objective model was presented for the material distribution routing problem in mixed manufacturing systems,and it was solved by a hybrid multi-objective evolutionary algorithm (HMOEA).The characteristics of the HMOEA are as follows:1) A route pool is employed to preserve the best routes for the population initiation; 2) A specialized best-worst route crossover (BWRC) mode is designed to perform the crossover operators for selecting the best route from Chromosomes 1 to exchange with the worst one in Chromosomes 2,so that the better genes are inherited to the offspring; 3) A route swap mode is used to perform the mutation for improving the convergence speed and preserving the better gene; 4) Local heuristics search methods are applied in this algorithm.Computational study of a practical case shows that the proposed algorithm can decrease the total travel distance by 51.66％,enhance the average vehicle load rate by 37.85％,cut down 15 routes and reduce a deliver vehicle.The convergence speed of HMOEA is faster than that of famous NSGA-Ⅱ.