Integration of Facility Location and Hypercube Queuing Models in Emergency Medical Systems

Ghobadi, Maryam; Arkat, Jamal; Farughi, Hiwa; Tavakkoli–Moghaddam, Reza

doi:10.1007/s11518-021-5500-x

Cited by 6 publications

(2 citation statements)

References 42 publications

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“…Other [92,119,111,185,2,57,183,106,182,136,122,177,95,148,76,77,98,109,39,91,63,90,116,162,161,149,25,46,8,56,6,72,150,164] arrival at the event site [37]) only becomes exactly known when the emergency patient is reached.…”

Section: Patientrelatedmentioning

confidence: 99%

Simulation optimization in healthcare resource planning: A literature review

Wang

Demeulemeester

2023

IISE Transactions

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In healthcare, the planning and the management of resources are challenging as there are always a number of complex and stochastic factors in both demand and supply. Simulation optimization (SO) that combines simulation analysis and optimization techniques is well suited for solving complicated, stochastic, and mathematically intractable decision problems. In order to comprehensively unveil the degree to which SO has been used to solve healthcare resource planning problems, this paper reviews the academic articles published until 2021 and categorizes them into multiple classification fields that are related to either problem perspectives (i.e., healthcare services, planning decisions, and objectives) or methodology perspectives (i.e., SO approaches and applications). We also examine the relations between the individual fields. We find that emergency care services are the most applied domain of SO, and that discrete-event simulation and random search methods (especially genetic algorithms) are the most frequently used methods. The literature classification can help researchers quickly learn this research area and identify the publications of interest. Finally, we identify major trends, insights and conclusions that deserve special attention when studying this area. We suggest many avenues for further research that provide opportunities for expanding existing methodologies and for narrowing the gap between theory and practice.

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Section: Patientrelatedmentioning

confidence: 99%

Simulation optimization in healthcare resource planning: A literature review

Wang

Demeulemeester

2023

IISE Transactions

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“…Tayal and Singh (2019) addressed the FLP from the point of a demand-based disaster for relief operations. Ghobadi et al (2021), in their study on the integration of facility location models in emergency medical systems, combined the decisions about the location and despatching policy by integrating the location and hypercube queuing models. For a detailed review of the combined framework for emergency facility location in transportation networks, one can refer to Liu et al (2021).…”

Section: Literature Reviewmentioning

confidence: 99%

Designing a drone assisted sample collection and testing system during epidemic outbreaks

Chakraborty

Nadar

Tiwari

2021

JGOSS

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Purpose A major component in managing pandemic outbreaks involves testing the suspected individuals and isolating them to avoid transmission in the community. This requires setting up testing centres for diagnosis of the infected individuals, which usually involves movement of either patient from their residence to the testing centre or personnel visiting the patient, thus aggregating the risk of transmission to localities and testing centres. The purpose of this paper is to investigate and minimize such movements by developing a drone assisted sample collection and diagnostic system. Design/methodology/approach Effective control of an epidemic outbreak calls for a rapid response and involves testing suspected individuals and isolating them to avoid transmission in the community. This paper presents the problem in a two-phase manner by locating sample collection centres while assigning neighbourhoods to these collection centres and thereafter, assigning collection centres to nearest testing centres. To solve the mathematical model, this study develops a mixed-integer linear programming model and propose an integrated genetic algorithm with a local search-based approach (GA-LS) to solve the problem. Findings Proposed approach is demonstrated as a case problem in an Indian urban city named Kolkata. Computational results show that the integrated GA-LS approach is capable of producing good quality solutions within a short span of time, which aids to the practicality in the circumstance of a pandemic. Social implications The COVID-19 pandemic has shown that the large-scale outbreak of a transmissible disease may require a restriction of movement to take control of the exponential transmission. This paper proposes a system for the location of clinical sample collection centres in such a way that drones can be used for the transportation of samples from the neighbourhood to the testing centres. Originality/value Epidemic outbreaks have been a reason behind a major number of deaths across the world. The present study addresses the critical issue of identifying locations of temporary sample collection centres for drone assisted testing in major cities, which is by its nature unique and has not been considered by any other previous literature. The findings of this study will be of particular interest to the policy-makers to build a more robust epidemic resistance.

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