Izvorni znanstveni članak

https://doi.org/10.17559/TV-20250418002604

MPPSO-Based Collaborative Optimization for Emergency Medical Supplies Loading and Scheduling

Hankun Zhang ; Business School, Beijing Technology and Business University, Beijing 100048, China
Jiayu Shen ; Business School, Beijing Technology and Business University, Beijing 100048, China
Jianna Yang ; Business School, Beijing Technology and Business University, Beijing 100048, China
Robert Ojstersek orcid.org/0000-0001-6244-3737 ; Faculty of Mechanical Engineering, University of Maribor, 2000 Maribor, Slovenia *

* Dopisni autor.

Sažetak

Public emergency occurs frequently, which has a serious impact on people's life safety and social stability. When public emergency occurs, the government needs to respond quickly to reduce casualties and property losses. Emergency medical supplies scheduling is the key work of government response, which is a scheduling problem. To solve the scheduling problem, firstly, we designed a collaborative system of loading and scheduling of emergency medical supplies. Secondly, considering the waiting time and the affected level of the affected point, and the conflict time of loading and unloading, a loading and scheduling collaborative optimization model of emergency medical supplies is constructed, the objective of which is the minimum maximum weighted time of all affected points. Thirdly, based on the Multi-phase Particle Swarm Optimization (MPPSO), an improved Multi-phase Particle Swarm Optimization (IMPPSO) is designed to improve the ability to solve the constructed collaborative optimization model. Finally, by taking the rainstorm event in Fangshan District on July 31, 2023 as an example, the proposed method has obtained an efficient scheduling solution in a reasonable time. The average fitness obtained by IMPPSO is 15,58% and 42,95% better than that of MPPSO and Particle Swarm Optimization (PSO), respectively. It is proved that the proposed method has good feasibility in practical application, which provides emergency medical supplies scheduling decision support for emergency management departments in public emergency.

Ključne riječi

emergency medical supplies; loading and scheduling collaborative; multi-phase particle swarm optimization; public emergency

Hrčak ID:

342632

URI

https://hrcak.srce.hr/342632

Datum izdavanja:

31.12.2025.

Posjeta: 383 *