Abstract: The urban medical waste demand increases greatly, which is also difficult to be determined accurately with the influence of many factors. Therefore, the model for urban medical waste recycling network design model with deterministic recycling demand might not match the actual demand. The problem that the location,assignment as well as transportation are optimized collaboratively is considered, and a two-stage stochastic programming model is built with minimizing the location cost and transportation cost as well as considering the facility and vehicle capacity constraints. And a benders decomposition algorithm is developed according to the model structure. In addition, a series of acceleration techniques are designed to improve the efficiency of this algorithm. Finally, the feasibility and effectiveness of the proposed model and solution strategy are verified through case studies which based on the certain city in China. The results show that the solution of stochastic programming can save more cost than the deterministic programming, and the benders decomposition method combined with a series of accelerating techniques has more advantages than the CPLEX and pure benders decomposition without any accelerating technique.

Key words: urban medical waste, network design, stochastic programming, benders decomposition, accelerating technique