Smart transportation solutions for faster emergency medical services response using an enhanced whale optimization algorithm

Abstract Emergency Medical Services (EMS) are vital for providing timely out‐of‐hospital care during medical emergencies. This research aims to optimize ambulance services by strategically allocating resources to minimize response time. A modified Whale Optimization Algorithm (mWOA) is introduced to achieve this goal, focusing on providing 24 × 7 services to every patient in need. The, conducted in Southern Delhi, India, considers the uncertain and stochastic nature of demand and traffic. The results demonstrate a 14.6% improvement in average EMS‐based response time, highlighting the effectiveness of the mWOA algorithm in enhancing ambulance allocation strategies. The results obtained using different algorithms are compared with those obtained using mWOA. The experiment outcomes demonstrate that the mWOA has higher efficiency and superiority than alternative algorithms regarding convergence rate and stability.

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Publication Details

Journal
IET Intelligent Transport Systems
Published
2024-09-19
DOI
https://doi.org/10.1049/itr2.12555
Citations
4
Primary Topic
Facility Location and Emergency Management
Type
article
Field-Weighted Citation Impact
2.70
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article

Smart transportation solutions for faster emergency medical services response using an enhanced whale optimization algorithm

Mohammad Amir, Furkan Ahmad, Ishaq G. Muhammad Alblushi, Haris M. Khalid et al.
4 citations
IET Intelligent Transport Systems
Facility Location and Emergency Management
2.70
article

Smart transportation solutions for faster emergency medical services response using an enhanced whale optimization algorithm

Mohammad Amir, Furkan Ahmad, Ishaq G. Muhammad Alblushi, Haris M. Khalid, Hina Gupta, Zaheeruddin
article en
4 citations

Abstract

Abstract Emergency Medical Services (EMS) are vital for providing timely out‐of‐hospital care during medical emergencies. This research aims to optimize ambulance services by strategically allocating resources to minimize response time. A modified Whale Optimization Algorithm (mWOA) is introduced to achieve this goal, focusing on providing 24 × 7 services to every patient in need. The, conducted in Southern Delhi, India, considers the uncertain and stochastic nature of demand and traffic. The results demonstrate a 14.6% improvement in average EMS‐based response time, highlighting the effectiveness of the mWOA algorithm in enhancing ambulance allocation strategies. The results obtained using different algorithms are compared with those obtained using mWOA. The experiment outcomes demonstrate that the mWOA has higher efficiency and superiority than alternative algorithms regarding convergence rate and stability.

IET Intelligent Transport SystemsVol. 18(12)
Higher Colleges of Technology (AE), University of Dubai (AE), University of Johannesburg (ZA), Bennett University (IN), Hamad bin Khalifa University (QA), Jamia Millia Islamia (IN), Qatar Foundation (QA)
Openalex Percentile: Top 9%
Facility Location and Emergency Management
2.70
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Smart transportation solutions for faster emergency medical services response using an enhanced whale optimization algorithm — Mohammad Amir, Furkan Ahmad, et al. · IET Intelligent Transport Systems (2024) | TGRS Research Map | TGRS