E-commerce Supply Chain Flexibility Research Based On Extreme Optimization

The economic globalization and Internet has tremendously facilitated the development of E-commerce, along with the focus of its corresponding supply chain. An important factor to maintain the rapid growth of E-commerce, therefore, is to establish the supply chain. This thesis has focused on the the modeling of E-commerce supply chain network based on the extreme optimization, and the analysis of its resilience.The paper first introduces the front-end and back-end logistics in E-commerce supply chain. Their current development status and shortcomings are then discussed. The research method to improve the shortcomings, extreme optimization, is talked about from its basics to its modification, and its potential problems in application.The mathematic model of supply network is built. Based on the analysis of loading and juncture satisfaction, the optimization has been achieved in both the individual and overall objectives. The network elasticity has been analyzed in its adaptability and recoverability. The classic case study of supply chain management, Toyota automobile, is taken to simulate and verify the validity of the algorithm.Due to the scarcity of quantitative simulation in back-end logistics research and inadequate consideration of the customized requirements in the modeling, this paper has established the model with the minimization of the per-capita costs as the objective. This model aims to reduce the distribution costs with improving service quality at the same time by combing the vehicle routing problem and the characteristics of multiple varieties, small quantity, large batches, and short duration of E-commerce consuming. Featuring the uncertainty of the client's daily demand, the elastic delivery strategy is proposed. The logistics routes have been optimized though improved ant colony algorithm. The converging efficiency has been improved by combing local and global search. The elasticity of multiple demand uncertainty has been validated to enhance the efficient distribution in back-end logistics.