Research Of Multi-product Multi-period Ordering Optimization Considering Inventory Service Level

With the proposal of new retailing,there is much more fierce competition in retail market online to offline.Therefore,improving the service level on one hand and reducing the operation cost in order to provide more attractive price on the other hand,has become the core issue for those company with price leadership strategy.Usually,reducing inventory is one of the most effective methods of reducing the operation cost.However,this might influence the customer's shopping experience and customer satisfaction because of the product shortage in stock.For the sake of optimum balance between inventory and service level,a high level of inventory management method must be required.As an important link of inventory management,order management for products is closely related to inventory management.Therefore,research of ordering strategy for retail enterprises has very important practical significance.The innovation of this paper is considering service level from the perspective of objective function,and established a dual objective mathematical programming model with the goal of minimizing total cost and maximizing service level.It designed nondominant sort genetic algorithm II to solve the model,and it was compared with traditional optimization model which considered service level constraint.The main research contents are as follows:This paper took the large-scale retail store with various types of products as an example,the multi-product ordering strategy of service level is considered from two aspects of constraint and goal.After analyzing the problem of multi-product multi-cycle ordering optimization,this paper found the following question:research on service level is based on time order method and safety inventory,they seldom set a value of a service level for the product,or even set the service levels as the goal to optimize.Based on this,the paper firstly established a mixed integer programming model based on time order method with multi constraints including inventory capacity,inventory balance,service level and so on.Firstly,the AMPL integrated development environment was used to solve the model and verify the accuracy of the model.In order to solve the problem of large-scale examples and the randomness of requirements,the genetic algorithm was designed to verify and solve the model,and the sensitivity analysis of service level and order cycle was also done.Next it analyzed the current inventory management situation of retail enterprises and the existing problems in the current management,and then divided the products by two-stage cluster analysis.To further optimize the service level,a dual objective mathematical programming model with the goal of minimizing total cost and maximizing service level was established,and the nondominant sort genetic algorithm ?(NSGA-?)was designed to optimize and solve the model.The application of the model was reflected through example analysis.Finally,the sensitivity analysis of inventory capacity was carried out.The ordering optimization model designed in this paper can provide certain reference for the inventory management decision-makers in order management.