Research On Emergency Orders Oriented Customized Supply Chain Scheduling

In today's dynamic business environment, consumer's loyalty to a single products is getting lower, at the same time, their demands for diversified is more obviously.In order to meet customer's diversity demands, more and more enterprises has been gradually shifting their production system style from traditional make-to-inventory to make-to-order. And provide customer manufacturing has become a very important development competitive strategy. In this kind of enterprise, a phenomenon that existence of a large number of urgent orders can not be ignored. There are two mainly reasons for this situation, one is customer's needs is not predicted, the other is the occurrence of disasters. This led the enterprises to face a large number of urgent customer orders, and make a great challenge for the normal production.Today, enterprises participate the market competition in the form of supply chain, so, I chose the supply chain scheduling to be my research perspective. Special tasks including the formation mechanism of the menergency customer orders,basic characteristics,the main bottleneck of scheduling processes and optimization methods。Further more, in order to verificate the research contents and results, I'll build the math model and use a real example to simulate and study the feasibility.Baced on the extensive literature study, first of all I'll summarize the emergency orders'features in the supply chain environment; analyze the formation mechanism of these characteristics. Second, explorat in-depthly the three bottlenecks which play the key role of these main features of emergency customer orders. Then use the graphics and algorithms to analyze the bottleneck, At the same time, give the targeted optimization methods for each problem. Third, based on the form work, eatablish the supply chain optimization scheduling model, set the minimum order's production time and cost as the objective function, to seek optimal scheduling strategy for emergency customer orders. Funally, use a actual production case, verify the feasibility of paper ideas and model construction, meanwhile considering about the scheduling optimization model and the ant colony algorithm.