Study On The Inventory Optimization And Pricing Strategy Of Omni-channel Supply Chain Network

The rapid development of the Internet has fundamentally changed the internal structure and business model of the supply chain network.The new retail mode of offline physical stores,PC online stores,online stores,live broadcast platforms has gradually formed the omni-channel supply chain network.The cross-channel and complexity of the supply-demand relationship in the omni-channel supply chain makes the network inefficient and bad coordination,especially the disorder of inventory system and the vicious competition of product pricing.In this thesis,it focuses on the optimization of the omni-channel supply chain network for the logistics system.It optimizes the inventory and pricing of the omni-channel supply chain network based on the prediction of the network nodes logistics volume,so as to improve the overall operation efficiency and internal coordination ability of the omni-channel supply chain network.The main research work and achievements are as follows:(1)Operation characteristics and mode of omni-channel supply chain network are analyzed.Based on the analysis of the internal structure,network structure and network hierarchy of the omni-channel supply chain network,this thesis analyzes the significant characteristics of the omni-channel supply chain network.It recognizes the high integration and complexity of the supply-demand relationship in the omni-channel supply chain network,and it analyzes the operation mode of the omni-channel supply chain network.It explores the influence of the multi-core radiation mode on the optimization of the omni-channel supply chain network.(2)Optimization factors of omni-channel supply chain network are decomposed.The network optimization elements of omni-channel supply chain are divided into nodes logistics volume,inventory control and product pricing.Among them,nodes logistics volume is the premise and basis for the study of inventory and pricing optimization.The network nodes need to optimize the inventory system reasonably according to the logistics volume prediction index.At the same time,the product pricing dynamically adjusts the pricing of each marketing channel based on the inventory cost.(3)Nodes logistics volume of omni-channel supply chain network is predicted.Logistics volume is not only the carrier of business transactions of nodes members in the supply chain network,but also an important bridge for enterprises to coordinate the logistics system.Nodes members can realize self-regulation of inventory and pricing decisions through reasonable control of network logistics volume.For the omni-channel supply chain network,the logistics relationship among the nodes is more complex,which puts forward higher requirements for the prediction method of logistics volume.The traditional shallow learning model is prominent in over fitting.Therefore,this thesis constructs the deep learning model to predict the nodes logistics volume of omnichannel supply chain network.(4)Inventory optimization model is build based on logistics volume prediction.The core of inventory optimization is to minimize the inventory cost by making the optimal order quantity and order time.In the omni-channel supply chain network,the demand rate of inventory system can be directly reflected by the network logistics volume.According to the demand rate and order batch in the previous order cycle,node enterprises make rational judgment on the demand rate in the next order cycle.Then,the stochastic inventory decision-making model is constructed to realize the supplydemand balance of the inventory system.(5)The pricing strategy of omni-channel supply chain network is proposed considering inventory factor.In this thesis,the network pricing and inventory optimization of omni-channel supply chain are linked.Under the condition of retailer's inventory optimization and product pricing,this thesis analyzes the interaction principle of price conflicts among different channels of network nodes,and it constructs a nonlinear programming method with retailer's revenue maximization as the objective function.When the customer demand is evenly distributed and the pricing strategy in each channel has an impact on the market demand of itself and other channels,there is Nash equilibrium in the pricing strategy of retailers in each channel.In a word,this thesis uses the omni-channel perspective,and the new Internet marketing channels such as mobile channels and social media channels are included in the study of supply chain network optimization.This thesis breaks the limitation of single channel or dual channel supply chain network,and the research problem is closer to the actual demand.This thesis applies the deep learning model to the supply chain network nodes logistics volume prediction.It constructs the stacked autoencoders intelligent prediction model.This model can abstract the essential characteristics of data through many parameters training,and the prediction results have the higher accuracy than the previous shallow neural network model.This thesis combines the logistics volume,inventory and pricing modeling,and it constructs a stochastic inventory decision-making model based on the nodes logistics volume prediction,aiming at inventory optimization.It solves the Nash equilibrium determination of retailers in different channels price.