A Novel Model and GA-Based Solution for Resource Scheduling in Highway Emergency Rescue
- DOI
- 10.2991/iceesd-18.2018.281How to use a DOI?
- Keywords
- Highway, Emergency Rescue, Vehicle Schedule, Genetic Algorithm
- Abstract
Highway is the major artery and main component of China's transportation system and plays a vital role in national economic construction. After an accident on the highway, how to quickly reach the accident point through effective dispatching and implementing emergency rescue operations is extremely important. Further, when the transportation conditions (such as traffic status) varies on different road segments at different time intervals, it is a very challenging problem to distinguish between priorities and properly dispatch emergency rescue resources. In this paper, it is taken as the key optimization goal to minimize the delay of emergency rescue response. And then, a genetic algorithm for solving the corresponding model is presented by adopting the random walk method. In our GA, a chromosome is represented by a transition matrix for defining the random walk, and specific crossover operation and mutation operation are given in details. The experiment on our GA is implemented by using GA-Toolbox of MATLAB, and the results manifest that our proposal is effective. Finally, the case of emergency rescue resource scheduling problem for the multiple accidents points is also discussed.
- Copyright
- © 2018, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Yuxin Niu PY - 2018/05 DA - 2018/05 TI - A Novel Model and GA-Based Solution for Resource Scheduling in Highway Emergency Rescue BT - Proceedings of the 2018 7th International Conference on Energy, Environment and Sustainable Development (ICEESD 2018) PB - Atlantis Press SP - 1549 EP - 1553 SN - 2352-5401 UR - https://doi.org/10.2991/iceesd-18.2018.281 DO - 10.2991/iceesd-18.2018.281 ID - Niu2018/05 ER -