Research On Inventory-routing Optimization Based On VMI

Vendor Managed Inventory(VMI)manages inventory through systematic and integrated thought,effectively alleviating the bullwhip effect and reducing supply chain operating costs.For suppliers,how to manage inventory and formulate a reasonable distribution plan,while ensuring that the total cost of the planning period of the system is minimum,is an urgent problem to be solved in implementing VMI strategy.Inventory-routing optimization based on VMI is to optimize the two logistics links of inventory and distribution under VMI mode.Based on the existing research,this paper studies the inventory-routing optimization problem with the goal of minimizing the total cost of the planning period under the background of VMI model,taking a two-stage supply chain system composed of one supplier and multiple retailers as the research object.Firstly,the research objectives,contents and train of thought of this paper are determined.By consulting domestic and foreign literature,this paper analyses the application of vendor managed inventory and the status quo of inventory-routing problem.On the premise of understanding the relevant theories of vendor managed inventory,inventory-routing problem,inventory strategy and distribution strategy,as well as genetic algorithm and saving algorithm,this paper puts forward the research objectives,research contents and research train of thought of this paper.Secondly,an inventory-routing optimization model based on VMI is established.Taking the retailer's inventory capacity and vehicle capacity limitation as constraints,a mixed-integer programming model with the objective of minimizing the total cost of the planning period in multiple periods with stochastic demand is constructed.When constructing the model,the distribution cost is refined.In addition to considering the start-up cost related to the number of vehicles and the driving cost related to the distribution distance,the labor cost related to the distribution time is increased,which is closer to the reality.Finally,the model algorithm is designed and an example is given to verify the effectiveness of the model and the algorithm.According to the model,a hybrid genetic algorithm formed by nested saving algorithm of genetic algorithm is designed,and combined with the sample mean approximation method and a specific example to solve the problem.It not only formulates a reasonable inventory strategy and distribution strategy for suppliers and retailers,that is,to determine the retailers' replenishment point,distribution volume and distribution routing,so as to reduce the total cost of the planning period,but also provides theoretical support for enterprise management decision-making.In addition,under the same environment,the results of joint optimization and decentralized decision-making are compared and analyzed.On the one hand,the necessity of joint optimization is verified;on the other hand,the effectiveness of hybrid genetic algorithm is verified to some extent,and the feasibility of the model is also reflected.