Two Server Dynamic Coverage Location Model Under Stochastic Travel Time

Naji, Huda Zaki; Al-Behadili, Mohanad; AL-Maliky, Ferhan

doi:10.1007/s40819-021-00950-6

Cited by 3 publications

(3 citation statements)

References 31 publications

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“…It also chose three 8-hour time periods for the proposed model, based on the peak and off-peak times. On the other hand, an EMS manager may establish the optimal length for each time period based on statistical analysis 2,35 . The MO-CL search algorithm is employed to meet the average coverage and ALS or…”

Section: Data Collection and Parameter Configurationmentioning

confidence: 99%

“…In such critical cases, there is a need to reduce the response time by imposing location and relocation restrictions on EMS facilities. However, the goals and limitations of situating or assigning EMS facilities based on the spatial arrangements 1,2 . The Facility Coverage Location Problem (FCLP) developed by Hotellin 3 , was one of the methodologies used to solve real-world problems.…”

Section: Introductionmentioning

confidence: 99%

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A Multi-Objective Facility Coverage Location Problem for Emergency Medical Service Decisions in Hajj

Naji,

Al-Behadili,

Kadim

2024

Baghdad Sci.J

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This paper proposes a multi-objective facility model of coverage location problem to determine the number, locations, and redeployments of Emergency Medical Services (EMS) system. The EMS runs with two types of ambulances, Basic Life Support (BLS) and Advance Life Support (ALS). The suggested Multi-objective Coverage Location model (MO-CL) considers a bi-objective function, which is minimizing the EMS costs and the fatigue of EMS crew members. This can be managed by reducing the number of redeployments for both types of ambulances while still providing the required coverage levels. The MO-CL model is based on the approximation hypercube model that eliminates the assumptions of autonomous ambulance operation and system-wide busy probability. It can be solved by applying a modified MO-CL search algorithm. The model and solution method have been applied for a case study based on real data collected from the Al Noor Specialist Hospital in Makkah, Saudi Arabia during the period of fifteen days of Hajj pilgrimage. The results showed that, to achieve the 95% coverage threshold of critical and non-critical demand, the MO-CL model needs at least 64 ambulances (29 ALS, 12 for BLS backups, and 23 for BLS) and 19 redeployments for every day (9 for ALS, 2 for BLS backup, and 8 for BLS).

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Section: Data Collection and Parameter Configurationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Multi-Objective Facility Coverage Location Problem for Emergency Medical Service Decisions in Hajj

Naji,

Al-Behadili,

Kadim

2024

Baghdad Sci.J

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“…They applied their model to a dataset based on the Coimbra district (Portugal) for locating 35 ambulances among 34 potential ambulance stations. Naji et al [49] propose a two-server dynamic covering location model to consider two types of patients and two types of servers.…”

Section: Marianov and Revellementioning

confidence: 99%

Ambulance location under temporal variation in demand using a mixed coded memetic algorithm

2022

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Emergency medical services (EMS) are among the most important services in any society due to their role in saving people's lives and reducing morbidities. The location of ambulance stations and the allocation of ambulances to the stations is an important planning problem for any EMS system to ensure adequate coverage while minimising the response time. This study considers a mixed-integer programming model that determines the ambulance locations by considering the time of day variations in demand. The presented model also considers heterogeneous performance measures based on survival function and coverage for different patient types with varying levels of urgency. A memetic algorithm based-approach that applies a mixed chromosome representation for solutions is proposed to solve the problem. Our computational results indicate that neglecting time-dependent variation of demand can underestimate the number of ambulances required by up to 15% during peak demand. We also demonstrate the effectiveness of the proposed solution approach in providing good quality solutions within a reasonable time.

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Adaptive variable neighbourhood search approach for time-dependent joint location and dispatching problem in a multi-tier ambulance system

Nadar

Jha

Thakkar³

2023

Computers & Operations Research

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Two Server Dynamic Coverage Location Model Under Stochastic Travel Time

Cited by 3 publications

References 31 publications

A Multi-Objective Facility Coverage Location Problem for Emergency Medical Service Decisions in Hajj

A Multi-Objective Facility Coverage Location Problem for Emergency Medical Service Decisions in Hajj

Ambulance location under temporal variation in demand using a mixed coded memetic algorithm

Adaptive variable neighbourhood search approach for time-dependent joint location and dispatching problem in a multi-tier ambulance system

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