Research on hierarchical emergency resource scheduling for island petrochemical enterprises based on improved multi-objective grey wolf optimization algorithm

Island petrochemical enterprises, as high-risk entities within the energy sector, face severe challenges in ensuring operational safety. Therefore, the ability to quickly and efficiently dispatch emergency resources after an accident occurs is crucial to prevent escalation of the situation. This paper constructs a hierarchical emergency resource scheduling model based on the hierarchical response to accidents in petrochemical enterprises, using an Improved Multi-objective Grey Wolf Optimization (IMOGWO) algorithm to solve the problem and optimize the emergency resource scheduling scheme. Key algorithm enhancements include a novel encoding method, incorporation of crossover and mutation operators to refine the predation strategy, and the use of Sobol sequences, reverse learning, and random disturbances for improved population initialization. Finally, taking a certain island petrochemical enterprise in China as an example, the effectiveness and practicality of the model were verified. Compared with the actual scheme, the optimized emergency resource scheduling scheme reduced the total cost by 38.50 % and the dispatch time by 20.81 % at the intra-factory level (enterprise). In terms of the extra-factory level (municipal), the total cost and the dispatch time were reduced by 25.33 % and 14.55 %, respectively. This study contributes to the sustainable and safe development of petrochemical enterprises for a secure energy future.