Abstract: With facility expansion, a multi-period, multi-product, multi-stage closed-loop logistics network model for used product collection and recycling is established. To minimize the total cost and maximize the responsiveness of the network, the location and allocation of the facilities in the network is implemented. A two-dimension array chromosome is adopted to represent the decision variables, and a two-stage procedure by using evolutionary and greedy algorithm is proposed to solve the multi-objective optimization problem. At last, a serial of numerical experiments is carried out to find the Pareto Solution Set and verify the proposed algorithm. Result shows that the performance of these two methods are nearly the same for small-scale problems, and the two-stage evolutionary algorithm is 10 times faster than CPLEX with a gap less than 8.24% when the scale of problems increases.

Key words: closed-loop logistics, evolutionary algorithm, facility location, multi-objective optimization