Research On Disruption Management Case Database Construction With Case-Based Reasoning

With increasing pressure to reduce cost and improve supply chain efficiency, there are more enterprises in supply chain spreading in larger regions. Simultaneously, there are less substitutive suppliers, manufacturers and distributers on horizontal supply chain nodes. As a result, the supply chains are becoming thinner and longer, which highly contributes to the vulnerability and uncertainty of supply chains. On the other hand, human being's economic activities have further extended and deepened in recent years. Environmental problems and pollutions are becoming fiercer and terrorism, workers strike and regional conflict are becoming more frequent. These disruptions are often sudden, abnormal, urgent and seriously lacking necessary information to deal with. The confliction between frequent disruptions and supply chain vulnerability is becoming fiercer nowadays, making both government and enterprises emphasize more on disruption classifying and management.Disruptions in the public management scope are divided into four categories– natural disasters, accidents, public health incidents and social security incidents, for the convenience of supervision and management from government departments of different levels and various functions. In contrast, disruption management in business administration area is still relatively less emphasized. Similar practices are risk management, including the monitoring, warning and handling of operational risks. Risk management also needs to deal with sudden and urgent emergencies, but these risks are usually not abnormal and seriously lacking information. The traditional disruption categories in government and enterprise management fields are overlapped and controversial, which arouses the need of a more general disruption classifying methodology. Considering the significant lack of knowledge and rules in this field, case-based reasoning method is especially beneficial for disruption management.Accordingly, based on the scope of disruptions breaking out and enterprise's view point, disruptions can be classified into four categories– gusty natural disasters, gusty public incidents, supply chain disruptions and enterprise disruptions. Thus the various disruptions in enterprises'business and government administration can be included.The fundamental and key steps in applying CBR are case indicating, case attributes reduction, case indexing and searching, case revising and learning. Frame method is applied to organize cases in clear structures, due to its structural, inheriting and natural style features. Information and knowledge in natural language and quantitative data can both be indicated with frame method, applying its inheriting feature between father-frame and child-frame. Case attributes need to be reduced to enhance the system efficiency when case amount is sharply increasing. Reluctant attributes would be contracted with a method based on information entropy. Entropy is applied to indicate the case classifying capability of different attributes, showing the relative importance of current attributes. Consequently, attributes of least importance could be removed after a careful analysis based on current knowledge.Lastly and most importantly, a combination of classified indexing, key words searching and KNN is creatively applied to the searching and matching process of disruption management cases, which significantly improved the system efficiency. This method can make high utilization of indexing attributes, text attributes and quantitative attributes respectively. The initial weights in KNN method can be scored by experts and analyzed with AHP. When the amount of cases significantly increases, attributes weights can be revised with method based on neural network method. Thus the hidden knowledge of cases could be well developed and utilized. In the process of case revising and learning, case re-instancing and induced replaying methods are applied to develop the system knowledge and improve system performance.MS Access is developed to indicate and store disruption management cases, among which the case indicating and searching modules are paid special attention. 6 database tables and some other supporting tables are developed to indicate cases structurally, while SQL inquiry and KNN algorithm are combined to execute the searching function.