关键词: 需求不确定, 订单分配, 不完全信息, 供应链模型

Abstract: As an important part of the supply chain model at the micro level, manufacturer's order allocation has a great influence on improving the efficiency of the supply chain. In the meanwhile, demand uncertainty, such as the policy cycle shortening and consumption patterns changing, increases the difficulty of the manufacturer's order allocation. However, supply chain management disruption caused by demand uncertainty has not been generally studied in the current literature. In order to maximize their profits or total supply chain profits under certain allocation rule, how supply chain participants should make decisions, which is discussed especially in this paper. Some positive explorations are made in order allocation models, which demand uncertainty is considered and incomplete information is introduced into the supply chain participants. Two kinds of the multi-suppliers and one-manufacturer models are analyzed within the method of proportional distribution under demand uncertainty. A supply chain model is emphasized on the study of decentralized decision and centralized decision based on complete information, which concludes that the latter can maximize the interest of supply chain because of the avoidance of marginal effect caused by one participant to another when making decisions. And then, another model is established upon incomplete information, which pays emphasis on the decision-making mechanism of manufacture based on its estimate of suppliers' private information with discounting factor and existing information. In addition, the risk tolerance of suppliers depends mainly on their production capacities and variable costs, and the intention of supplier getting order is proportional to the risk tolerance, inversely to the unit punishment. Finally, the aforementioned two models are validated by an example of demand obeying normal distribution, given that the demand of most goods is normal distribution in real life.

Key words: demand uncertainty, order allocation, incomplete information, supply chain model