TY - GEN
T1 - Node Dependency in Multi-Commodity Flow Problem with Applications to Transportation Networks
AU - Dai, Weibin
AU - Zhang, Jun
AU - Sun, Xiaoqian
AU - Wandelt, Sebastian
N1 - Publisher Copyright:
© 2016 ASCE.
PY - 2016
Y1 - 2016
N2 - In this research, we study the multi-commodity flow problem (MCFP) in the context of air transportation systems. MCFP deals with assigning a variety of goods to flow from sources to their destinations in a network. While many optimization problems in transportation networks can be formulated as a classic MCFP, previous research has mostly considered the edge capacity as a network flow constraint. Based on a traditional path-flow model and edge-flow model, this research proposes new modifications with the consideration of node capacity in the network. In addition, we implement new optimization heuristics improving the path-finding stage of the algorithm. These optimizations allow us to solve the MCFP for networks with around one hundred nodes. Based on these results, we define and compute the node-dependency relationship in MCFP networks. For preliminary evaluation, our novel techniques are evaluated on an air transportation network consisting of 164 nodes. The experiment showed that dependencies on a node are the results of joint influence of the network structure factors and flows. Moreover, the dependencies in our network come in geographical clusters.
AB - In this research, we study the multi-commodity flow problem (MCFP) in the context of air transportation systems. MCFP deals with assigning a variety of goods to flow from sources to their destinations in a network. While many optimization problems in transportation networks can be formulated as a classic MCFP, previous research has mostly considered the edge capacity as a network flow constraint. Based on a traditional path-flow model and edge-flow model, this research proposes new modifications with the consideration of node capacity in the network. In addition, we implement new optimization heuristics improving the path-finding stage of the algorithm. These optimizations allow us to solve the MCFP for networks with around one hundred nodes. Based on these results, we define and compute the node-dependency relationship in MCFP networks. For preliminary evaluation, our novel techniques are evaluated on an air transportation network consisting of 164 nodes. The experiment showed that dependencies on a node are the results of joint influence of the network structure factors and flows. Moreover, the dependencies in our network come in geographical clusters.
UR - https://www.scopus.com/pages/publications/84979760347
U2 - 10.1061/9780784479896.181
DO - 10.1061/9780784479896.181
M3 - Conference contribution
AN - SCOPUS:84979760347
T3 - CICTP 2016 - Green and Multimodal Transportation and Logistics - Proceedings of the 16th COTA International Conference of Transportation Professionals
SP - 1989
EP - 2001
BT - CICTP 2016 - Green and Multimodal Transportation and Logistics - Proceedings of the 16th COTA International Conference of Transportation Professionals
A2 - Ge, Ying-En
A2 - Wang, Xiaokun
A2 - Zhang, Yu
A2 - Huang, Youfang
PB - American Society of Civil Engineers (ASCE)
T2 - 16th COTA International Conference of Transportation Professionals: Green and Multimodal Transportation and Logistics, CICTP 2016
Y2 - 6 July 2016 through 9 July 2016
ER -