Abstract: Aiming at the material distribution routing optimization problem under uncertain job shop environment, the bottleneck index and bottleneck shifting index which represent the relative production load of each manufacturing unit and its the change trend are adopted to denote the time-varying distribution priority of the manufacturing unit. Then the time-varying material distribution routing optimization models are established and its objective is minimizing the distribution cost including vehicle transportation cost and punishment cost due to the violation of distribution priority. Based on that, suppose the condition that the vehicle haven’t to be loaded fully and material can be distributed to one manufacturing more times in order to guarantee that the material in the vehicle is distributed totally before the vehicle comes back to the distribution center and to avoid unnecessary distribution sub-route, then propose the modified time-varying material distribution routing optimization model to enhance the distribution productivity and decrease the distribution cost further. The greedy-based genetic algorithm is presented to solve the proposed optimization model. An example of some job shop material distribution routing optimization is given to prove the validation and practicability of the proposed method under uncertainty.

Key words: distribution routing optimization, greedy-based genetic algorithm, material separation, shifting bottleneck, time-varying material distribution