Network vulnerability analysis in time-space dimension

• Main Authors: Sean Chen, 陳昇
• Other Authors: Shang-Yao Yen
• Format: Others
• Language: zh-TW
• Published: 2019
• Online Access: http://ndltd.ncl.edu.tw/handle/sv7b87

碩士 === 國立中央大學 === 土木工程學系 === 107 === Back in the days, the network problems were mostly discussed in the spatial dimension academically, and the main research objects were arcs and nodes. The parameter adjustment of the model was mainly based on sensitivity analysis. In view of this, this study introduces the concept of time-space dimension, expands the network problem, uses the time-space network flow technique to establish an optimization model, and develops vulnerability analysis. Considering the value of the real-world, such as the peak moment characteristics of the transportation field, this study extends the research objects from arcs and nodes to the transportation system, including the routes (arcs) and stations (nodes) and cars (components). It is not only the change of the parameter weights, but also makes nodes or arcs can be closed which designed at a certain time point, and the changes of the transportation system in different time and space can be obtained from the viewpoint of system optimization, so that the analysis can be more accurate and provide better decisions for users in the future. This study develops vulnerability analysis and refers to Yan & Chen (2002), a scheduling model and a solution algorithm for inter-city bus carriers. From the standpoint of inter-city bus company, it designs a fleet scheduling model that integrates passenger trip demands and bus trip supplies, and uses multiple time-space network flow techniques to establish a model to optimize in time-space dimension, and get the best fleet schedule to serve passengers. About solution method, different from the previous research, the Lagrangian algorithm is used to solve the problem, this study uses the C++ programming language and the mathematical programming software CPLEX to solve the model. Finally, for the practical performance to evaluate model, the case study is regarding the operation data of inter-city bus company in Taiwan, and the vulnerability analysis is carried out for different parameters and variables to explore the influence of the changes in different time and space on the system optimization results.