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

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.

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Publication Details

Journal
Tehnicki vjesnik - Technical Gazette
Published
2025-12-30
DOI
https://doi.org/10.17559/tv-20250418002604
Primary Topic
Facility Location and Emergency Management
Type
article
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article

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

Robert Ojsteršek, Hankun Zhang, Jiayu Shen, Jianna Yang
Tehnicki vjesnik - Technical Gazette
Facility Location and Emergency Management
article

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

Robert Ojsteršek, Hankun Zhang, Jiayu Shen, Jianna Yang
article en

Abstract

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.

Tehnicki vjesnik - Technical GazetteVol. 33(1)
Beijing Technology and Business University (CN), University of Maribor (SI)
Openalex Percentile: Top 23%
Facility Location and Emergency Management
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