Post-disaster transportation of seriously injured people to hospitals

Shavarani, Seyed Mahdi; Vízvári, Béla

doi:10.1108/jhlscm-12-2017-0068

Cited by 12 publications

(18 citation statements)

References 90 publications

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“…Due to Np-harness of FLPs [46], metaheuristic algorithms are widely used to solve them. Genetic algorithms (GA) are among the most frequently used algorithms in the literature [47], [48]. Genetic Algorithm provides competitive solutions with less CPU time compared with other algorithms used in this area such as particle swarm, ant colony and simulated annealing [49]- [51].…”

Section: Solution Methodsmentioning

confidence: 99%

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Multi-level facility location-allocation problem for post-disaster humanitarian relief distribution

Shavarani¹

2019

JHLSCM

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Purpose Previously use of drones as a relief distribution vehicle was studied in several studies where required number of drones and the best locations for the relief centers were investigated. The maximum travel distance of drones without a need to recharge is limited by their endurance. Recharge stations can be used to extend the coverage area of the drones. The purpose of this paper is to find the best topology for both relief centers and recharge stations to cover a large-scale area with minimum and feasible incurred costs and waiting times. Design/methodology/approach A multi-level facility location problem (FLP) is utilized to find the optimum number of relief centers and refuel stations and their locations. It is supposed that the demand occurs according to Poisson distribution. The allocation of the demand is based on nearest neighborhood method. A hybrid genetic algorithm is proposed to solve the model. The performance of the algorithm is examined through a case study. Findings The proposed method delivers increased efficiency and responsiveness of the humanitarian relief system. The coverage area of the drones is extended by refuel stations, total costs of the system are reduced and the time to respond an emergency, which is an important factor in survival rate, is significantly decreased. Originality/value This study proposes a multi-level FLP to simultaneously account for recharge stations, relief centers and the number of required drones to cover all the demand for relief in a post-disaster period.

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Section: Solution Methodsmentioning

confidence: 99%

“…Taguchi method is used to tune the algorithm and find the best values for each of these parameters. The details of Taguchi methods can be found in many studies such as [47], [48], [53]…”

Section: Solution Methodsmentioning

confidence: 99%

Multi-level facility location-allocation problem for post-disaster humanitarian relief distribution

Shavarani¹

2019

JHLSCM

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“…The problem of rescuing injured victims in the time of a disaster is studied by [159] in the form of non fix Multi Depot Pickup and Delivery VRP (MDPDVRP), where the survival rate of the victim is maximised. In this problem, simple assumptions are taken such as the homogeneity of the vehicle with fixed speed and capacity.…”

Section: Hybrid Methods In Rescue Vrpsmentioning

confidence: 99%

“…As a general trend, it could be seen that most work addressed split delivery, such as in [34,42,46,47,[49][50][51]61,71,73,75,76,78,81,83,85,87,94,96,102,116,123,128,158] and multi-trip VRP that can be seen in [31,47,50,61,76,88,90,94,97,98,124,126,129], ref. [134,149,159] normally stressed on the problem of vehicle limitations such as the numbers of vehicle or the fuel limitation. However some works addressed the VRP in this scope by assuming flexible fleet size such as [30,87].…”

Section: Current Trendsmentioning

confidence: 99%

Vehicle Routing Optimisation in Humanitarian Operations: A Survey on Modelling and Optimisation Approaches

et al. 2021

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The growing field of humanitarian operations is driven by frequent events of disasters seen in the world today. Within this field, Operations Research (OR) plays a critical role in alleviating the suffering of victims that are impacted by disasters. This paper focuses on the branch of a well-known OR problem, known as the Vehicle Routing Problem (VRP), within the selected scope of humanitarian operations. A total of 123 papers of the last decade are reviewed and classified under the humanitarian operations of supply and delivery, evacuation as well as rescue operations. Besides specific disaster management phases and disaster types, various modelling challenges are highlighted, hinting towards a richer and more complex VRP seen under selected model characteristic classifications. Furthermore, established solution approaches, including hybrid solutions, are highlighted and classified, discussing how they are applied in the context of these humanitarian operations. The inclusion of a machine learning solution approach under the same classification is proposed. Finally, the trend and future outlook of VRP for the suggested humanitarian operations are discussed and highlighted.

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“…Logistics planning for an emergency includes the assignment of human resources and equipment to facilities, with the aim of accelerating relief distribution to affected areas. Categorizing the victims in need of medical care contributes to an optimized resource utilization [16] and proper allocation of rescue units to different categories decreases the rate of casualties [17]- [19]. Martí et al(2009) addressed this issue using mobile electronic triage tags to collect information from victims and allocate medical resources to them in real time.…”

Section: Introductionmentioning

confidence: 99%

Assignment of Medical Staff to Operating Rooms in Disaster Preparedness: A Novel Stochastic Approach

Shavarani

Golabi

Vízvári

2020

IEEE Trans. Eng. Manage.

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Following a large-scale disaster in a highly populated city, one can expect a large number of injured people to need urgent operation. If it can be assumed that the city in question is likely to experience a disaster (although the time of its occurrence is unknown), pre-disaster measures should be taken to mitigate the consequences of the disaster. This study aims to minimize the fatality rate through the proper assignment of operating room personnel to hospitals, such that both the expected value of the functioning operating rooms and the expected value of the service level are maximized. Service level is defined as a variable that has a negative relationship to the distance a patient is expected to travel in order to receive the required medical services. The probability of survival, for both personnel and operating rooms, depends on several stochastic factors. A bi-objective mixed integer nonlinear model is proposed for the problem. A simulated annealing algorithm, particle swarm and a genetic algorithm are developed to solve the model using a weighted metric method. The model is applied to a possible worst-case earthquake scenario in Tehran. The results show that the proposed approach significantly improves the performance of post-disaster emergency relief.

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Post-disaster transportation of seriously injured people to hospitals

Cited by 12 publications

References 90 publications

Multi-level facility location-allocation problem for post-disaster humanitarian relief distribution

Multi-level facility location-allocation problem for post-disaster humanitarian relief distribution

Vehicle Routing Optimisation in Humanitarian Operations: A Survey on Modelling and Optimisation Approaches

Assignment of Medical Staff to Operating Rooms in Disaster Preparedness: A Novel Stochastic Approach

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