Design of emergency response manufacturing networks: a decision-making framework

Haddad, Yousef; Salonitis, Konstantinos; Emmanouilidis, Christos

doi:10.1016/j.procir.2021.01.068

Cited by 5 publications

(4 citation statements)

References 7 publications

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“…In summary, current studies on facility siting problems mainly focus on the location of supply chain dispatch centers [14,24,25,28] and urban public medical/security service facilities [6,[14][15][16][19][20][21][34][35][36]. In the field of transportation, facility siting methods are mainly applied to road traffic [10,15,19,20], and research on emergency facility siting problems for railroads [22] is few and in the initial stage.…”

Section: Better Adaptation To Various Application Scenariosmentioning

confidence: 99%

Optimal Location of Emergency Facility Sites for Railway Dangerous Goods Transportation under Uncertain Conditions

Wang

Chen

et al. 2023

Applied Sciences

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Railroad accidents involving dangerous goods (DG) need to be rescued quickly due to their hazardous nature. This paper proposes an emergency facility location model for the railway dangerous-goods transportation problem (RDGT-EFLP, abbreviated as EFLP). The EFLP model is based on an ellipsoidal robust model that introduces a robust control safety parameter Ω to measure the risk preferences of decision makers and limits the range of uncertain demand, the range of uncertain service and the range of safety parameters to find the solution for siting emergency facilities, when the time and location of emergency events are unknown. The model is solved using a genetic algorithm (GA) and real data after abstraction. Finally, a comprehensive analysis of the solution results under different maximum overcoverages illustrates the feasibility and effectiveness of the model.

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Section: Better Adaptation To Various Application Scenariosmentioning

confidence: 99%

Optimal Location of Emergency Facility Sites for Railway Dangerous Goods Transportation under Uncertain Conditions

Wang

Chen

et al. 2023

Applied Sciences

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“…Single Tang et al [93] Discrete event simulation Nepomuceno et al [81] Data envelopment analysis (DEA) Mehrotra et al [77] Stochastic optimization AbdelAziz et al [40] Multi-objective pareto optimization Peng et al [85]; Moss et al [80] Simulation Aggarwal et al [41] Additive utility assumption Araz et al [45] System dynamics Hybrid Garbey et al [62] Markov chains, stochastic optimization Albahri et al [42] Entropy, TOPSIS De Nardo et al [58] Potentially all pairwise ranking of all possible alternatives (PAPRIKA), multi-criteria decision making (MCDM) Parker et al [84] Linear programming, mixed-integer programming Zeinalnezhad et al [98] Colored petri nets, discrete event simulation Zhang & Cheng. [100] Logistic regression, Markov chains Abadi et al [39] Hybrid salp swarm algorithm and genetic algorithm (HSSAGA) Haddad et al [67] Simulation, optimization…”

Section: Authors Technique Typementioning

confidence: 99%

“…Their analysis confirmed that the current workflow was not optimal for COVID-19 patients; three optimization scenarios were therefore proposed to reduce the waiting time problem. In a different study, Haddad et al [67] crafted a decision-making approach for the creation of local emergency response manufacturing networks reducing shortages of medical supplies in times of COVID-19 crisis. In this work, interrelated simulation and stochastic models are applied to optimize the ventilator allocation in USA emergency departments considering uncertainty.…”

Section: Authors Technique Typementioning

confidence: 99%

Process Improvement Approaches for Increasing the Response of Emergency Departments against the COVID-19 Pandemic: A Systematic Review

Ortíz‐Barrios

Coba-Blanco

Alfaro-Saiz

et al. 2021

IJERPH

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The COVID-19 pandemic has strongly affected the dynamics of Emergency Departments (EDs) worldwide and has accentuated the need for tackling different operational inefficiencies that decrease the quality of care provided to infected patients. The EDs continue to struggle against this outbreak by implementing strategies maximizing their performance within an uncertain healthcare environment. The efforts, however, have remained insufficient in view of the growing number of admissions and increased severity of the coronavirus disease. Therefore, the primary aim of this paper is to review the literature on process improvement interventions focused on increasing the ED response to the current COVID-19 outbreak to delineate future research lines based on the gaps detected in the practical scenario. Therefore, we applied the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to perform a review containing the research papers published between December 2019 and April 2021 using ISI Web of Science, Scopus, PubMed, IEEE, Google Scholar, and Science Direct databases. The articles were further classified taking into account the research domain, primary aim, journal, and publication year. A total of 65 papers disseminated in 51 journals were concluded to satisfy the inclusion criteria. Our review found that most applications have been directed towards predicting the health outcomes in COVID-19 patients through machine learning and data analytics techniques. In the overarching pandemic, healthcare decision makers are strongly recommended to integrate artificial intelligence techniques with approaches from the operations research (OR) and quality management domains to upgrade the ED performance under social-economic restrictions.

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“…This reflects that there are some shortcomings and defects in somatic cells of emergency supplies in various countries suffering epidemics 1 , 2 . In the process of multi-scenario risk decision-making, the decision-maker has a certain prediction on the attribute value, which is completely rational expected utility, but the decision-maker, in reality, is finitely rational 3 , 4 .…”

Section: Introductionmentioning

confidence: 99%

Decision optimization of emergency material support based on blockchain under major public health emergencies

Wang

Fan

KunBao

2022

Sci Rep

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The work intends to relieve the pressure on the urban medical system and reduce the cross-infection of personnel in major public health emergencies. On the premise of an in-depth analysis of the utility risk entropy algorithm model and prospect theory, the decision-making of major health emergencies is proposed. Firstly, the utility risk entropy algorithm model is optimized, and the main decision-making members are subjected to utility perception according to the perceived utility values of different levels of risk, and the weights of decision-making members are calculated and revised according to the results of utility clustering. Secondly, the prospect theory is optimized. Taking the zero as the reference point to calculate the prospect value, and taking the maximization of the comprehensive prospect value as the objective to optimize the model, the comprehensive prospect value of each scheme is calculated and sorted. Finally, the proposed scheme is tested, and the test results show that in the optimal decision-making time of the scheme, the optimal decision-making time is 0 every day. When the epidemic situation is in the first cycle, the decision-making loss of the optimal scheme is 2.69, and the reduction ratio of the optimal scheme decision-making loss is 63.96%. When the epidemic situation is in the second cycle, the decision-making loss of the optimal scheme is 0.65, and the reduction ratio of the optimal scheme decision-making loss is 94.44%. When the epidemic situation is in the third cycle, the decision-making loss of the optimal scheme is 0.22, and the reduction ratio of the decision-making loss of the optimal scheme is 89.39%. The proposed scheme can improve the processing efficiency of major health emergencies and reduce the risk of accidents.

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Design of emergency response manufacturing networks: a decision-making framework

Cited by 5 publications

References 7 publications

Optimal Location of Emergency Facility Sites for Railway Dangerous Goods Transportation under Uncertain Conditions

Optimal Location of Emergency Facility Sites for Railway Dangerous Goods Transportation under Uncertain Conditions

Process Improvement Approaches for Increasing the Response of Emergency Departments against the COVID-19 Pandemic: A Systematic Review

Decision optimization of emergency material support based on blockchain under major public health emergencies

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