Supermarket Supply Chain Management System Design And Performance Optimization

The modern information science and technology are developed rapidly. In thesupermarket retail industry,the use of the information management and supply chainmanagement have caused wide attention. How to effectively use the intelligentmanagement of supply chain and recommend is very important to reduce the cost andimprove economic benefits. This thesis designs the supermarket Supply Chainmanagement system,comprehensive use of the BP neural network algorithm, databasemanagement, the supply chain management and so on, starting from the actualdemand of supermarket, to strengthen the ablity of supermarket informationmanagement and supply chain optimization,the thesis provided a reliable solution.The design scheme of the intelligent management system includes two parts ofhardware configuration and software development. Hardware configuration is mainlyincluding servers, switches, routers, hubs, more clients, etc. System softwaredevelopment used C/S architecture, the thesis uses oracle10g and labview2013todevelop the system.using labview development is for the sake of consistent andsupermarket consumption system, broadcasting system,etc, in order to centralizedmanagement.Background database software is oracle10g, which is used to store aseries of supermarket management information data.In the level of the optimization of supply chain, supply chain uses the skill of BPneural network algorithm to predict instead of economic order quantity model inmicroeconomics.the thesis uses the method of prediction of the quantity of goods tocontrol the quantity of the supermarket inventory,so it makes the supermarketinventory in a reasonable scope and no longer redundancy or out of stock,and it can reduce the cost in the supermarket operation,and increase profits. In supply chainmanagement level,realizing the prediction of replenish onr’s stock is one of thedifficulties and innovations of this thesis. This thesis predicts the supply chain basedon the BP neural network algorithm,before analysis, the thesis used economic orderquantity model in microeconomics to predict, the minimum error rate is1.22%, themaximum error rate reached19.24%, after using the skill of the BP neural networkalgorithm, minimum error rate reached almost0, maximun error rate was6.72%,the error rate dropped by12.52%, This method is more in line with the reasonablecontrol of the supermarket inventory.By contrast, the thesis founds that the supermarket supply chain managementperformance is better than before, inventory is no longer redundant or out of stock asbefore, which makes the quality of the supermarket further improved.