TY  - JOUR
AU  - Li, Feng
AU  - Lv, Jiahong
PY  - 2026
DA  - 2026/04/21
TI  - Multi-Objective Optimization for Emergency Material Dispatch with Backup Centers in Earthquake-Induced Distribution Failures Using Improved NSGA-II
JO  - ICCK Transactions on Intelligent Systematics
T2  - ICCK Transactions on Intelligent Systematics
JF  - ICCK Transactions on Intelligent Systematics
VL  - 3
IS  - 2
SP  - 108
EP  - 125
DO  - 10.62762/TIS.2025.202079
UR  - https://www.icck.org/article/abs/TIS.2025.202079
KW  - emergency material dispatch
KW  - distribution center failure
KW  - material distribution fairness
KW  - non-dominated sorting genetic algorithm
AB  - Earthquakes pose significant risks to infrastructure and supply chains, making the timely and fair distribution of emergency relief materials crucial for reducing casualties and economic losses. This study addresses the challenge of optimizing emergency material dispatch under scenarios where distribution centers fail due to earthquake damage, with the aim of improving both the timeliness and fairness of resource allocation during post-disaster recovery. A multi-objective optimization model is developed, which integrates distribution center failures and the activation of backup centers. The model minimizes total dispatch time, maximizes fairness in supply distribution, and reduces unmet demand. The solution is based on a second-generation non-dominated sorting genetic algorithm (NSGA-II), which is tailored to solve the proposed scheduling problem. Case studies, including simulations based on the 2008 Wenchuan earthquake, demonstrate that activating alternative distribution centers when primary centers fail can significantly improve delivery efficiency, fairness in material distribution, and reduce unmet demand. The improved NSGA-II algorithm outperforms the basic NSGA-II in terms of both solution quality and diversity. The findings underscore the importance of optimizing emergency logistics under failure scenarios to improve rescue efficiency and fairness. The model offers a scientifically-grounded approach for decision-making bodies to enhance post-disaster logistics operations, ensuring timely and equitable distribution of resources.
SN  - 3068-5079
PB  - Institute of Central Computation and Knowledge
LA  - English
ER  - 

@article{Li2026MultiObjec,
  author = {Feng Li and Jiahong Lv},
  title = {Multi-Objective Optimization for Emergency Material Dispatch with Backup Centers in Earthquake-Induced Distribution Failures Using Improved NSGA-II},
  journal = {ICCK Transactions on Intelligent Systematics},
  year = {2026},
  volume = {3},
  number = {2},
  pages = {108-125},
  doi = {10.62762/TIS.2025.202079},
  url = {https://www.icck.org/article/abs/TIS.2025.202079},
  abstract = {Earthquakes pose significant risks to infrastructure and supply chains, making the timely and fair distribution of emergency relief materials crucial for reducing casualties and economic losses. This study addresses the challenge of optimizing emergency material dispatch under scenarios where distribution centers fail due to earthquake damage, with the aim of improving both the timeliness and fairness of resource allocation during post-disaster recovery. A multi-objective optimization model is developed, which integrates distribution center failures and the activation of backup centers. The model minimizes total dispatch time, maximizes fairness in supply distribution, and reduces unmet demand. The solution is based on a second-generation non-dominated sorting genetic algorithm (NSGA-II), which is tailored to solve the proposed scheduling problem. Case studies, including simulations based on the 2008 Wenchuan earthquake, demonstrate that activating alternative distribution centers when primary centers fail can significantly improve delivery efficiency, fairness in material distribution, and reduce unmet demand. The improved NSGA-II algorithm outperforms the basic NSGA-II in terms of both solution quality and diversity. The findings underscore the importance of optimizing emergency logistics under failure scenarios to improve rescue efficiency and fairness. The model offers a scientifically-grounded approach for decision-making bodies to enhance post-disaster logistics operations, ensuring timely and equitable distribution of resources.},
  keywords = {emergency material dispatch, distribution center failure, material distribution fairness, non-dominated sorting genetic algorithm},
  issn = {3068-5079},
  publisher = {Institute of Central Computation and Knowledge}
}