TY - GEN
T1 - Research on Maritime Multi-center Emergency Resource Scheduling Based on Improved NSGA-II
AU - Wang, Yifan
AU - Geng, Qingbo
AU - Fei, Qing
AU - Wang, Bo
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - In order to provide effective support for maritime accidents, it is significant to study the maritime emergency resource scheduling. In this paper, considering that the existing scheduling model is difficult to apply to the maritime background, or the existing model considers insufficient factors, we propose a maritime multi-center emergency resource scheduling model. The model takes time penalty and total replenishment cost as targets, and introduces the influence of various environmental factors. Then, an improved non-dominated sorting genetic algorithm II (NSGA-II) is designed to optimize the model. In the algorithm, the population diversity is ensured by the improvement of population initialization and mutation operator, and an adaptive parameter adjustment strategy is adopted to improve the search efficiency. Simulation experiments show that the improved NSGA-II algorithm has better convergence and distribution, and the solution results also verify the correctness of the model.
AB - In order to provide effective support for maritime accidents, it is significant to study the maritime emergency resource scheduling. In this paper, considering that the existing scheduling model is difficult to apply to the maritime background, or the existing model considers insufficient factors, we propose a maritime multi-center emergency resource scheduling model. The model takes time penalty and total replenishment cost as targets, and introduces the influence of various environmental factors. Then, an improved non-dominated sorting genetic algorithm II (NSGA-II) is designed to optimize the model. In the algorithm, the population diversity is ensured by the improvement of population initialization and mutation operator, and an adaptive parameter adjustment strategy is adopted to improve the search efficiency. Simulation experiments show that the improved NSGA-II algorithm has better convergence and distribution, and the solution results also verify the correctness of the model.
KW - NSGA-II
KW - emergency resource scheduling
KW - multi-center
KW - multi-objective optimization
UR - http://www.scopus.com/inward/record.url?scp=85151151266&partnerID=8YFLogxK
U2 - 10.1109/CAC57257.2022.10055807
DO - 10.1109/CAC57257.2022.10055807
M3 - Conference contribution
AN - SCOPUS:85151151266
T3 - Proceedings - 2022 Chinese Automation Congress, CAC 2022
SP - 3389
EP - 3394
BT - Proceedings - 2022 Chinese Automation Congress, CAC 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 Chinese Automation Congress, CAC 2022
Y2 - 25 November 2022 through 27 November 2022
ER -