In this paper, we develop a model for emergency repair problems under large-scale supply-demand perturbations. The model formulation proposed in this paper has the following key features. First, a novel time-space network flow technique is adopted to generate detailed schedules for repair teams and allow dynamic updates of the network due to perturbations. Second, the original schedules prior to the perturbations are considered by controlling the total difference between the original schedule and the adjusted schedule. Third, to reduce computational complexity, the model is formulated with different levels of detail (individual teams versus a team group). The model is also formulated as a special mixed-integer network flow problem with side constraints, which is characterized as NP-hard. An ant-colony-system-based hybrid global search algorithm is developed to efficiently solve large-scale problems. To test how well the model formulation and the heuristic algorithm may perform in actual operations, we conduct a case study using actual data from the 1999 Chi-Chi earthquake in Taiwan. The results show that the proposed model and solution algorithm perform very well and thus have great potential for assisting with the making of emergency repair decisions in the event of disasters given large-scale perturbations in supply and demand.
|Number of pages||16|
|Journal||IEEE Transactions on Intelligent Transportation Systems|
|Publication status||Published - 2014 Dec 1|
All Science Journal Classification (ASJC) codes
- Automotive Engineering
- Mechanical Engineering
- Computer Science Applications