双渠道多级分销网络选址-库存问题

Aiming at the practical demand of the coexistence of each node's independent decision-making of and global optimization in the distribution network, the Analytical Target Cascading (ATC) was introduced to solve the location-inventory problem of multi-echelon distribution network. A multi-echelon, multi-node and multi-agent three-level problem solving model was constructed, and the strategy of convergence at the bottom and local genetic algorithm was used to coordinate the solution, so as to realize the location decision, inventory decision and online demand distribution decision. Taking the dual channel distribution network operation mode of a red wine enterprise as an example, the result of the location-inventory model was analyzed, and the solution result was compared with the traditional integrated optimization method. The effectiveness of ATC in solving the location-inventory problem was verified. Through the sensitivity analysis of the changes in variance, the results showed that the supply chain structure should be optimized in time and the level of online demand distribution should be adjusted to reduce the impact of demand uncertainty on the total logistics cost of enterprises.