scholarly journals Integrating Cluster Analysis into Multi-Criteria Decision Making for Maintenance Management of Aging Culverts

Mathematics ◽  
2021 ◽  
Vol 9 (20) ◽  
pp. 2549
Author(s):  
Francesca Marsili ◽  
Jörg Bödefeld

Negligence in relation to aging infrastructure systems could have unintended consequences and is therefore associated with a risk. The assessment of the risk of neglecting maintenance provides valuable information for decision making in maintenance management. However, infrastructure systems are interdependent and interconnected systems of systems characterized by hierarchical levels and a multiplicity of failure scenarios. Assessment methodologies are needed that can capture the multidimensional aspect of risk and simplify the risk assessment, while also improving the understanding and interpretation of the results. This paper proposes to integrate the multi-criteria decision analysis with data mining techniques to perform the risk assessment of aging infrastructures. The analysis is characterized by two phases. First, an intra failure scenario risk assessment is performed. Then, the results are aggregated to carry out an inter failure scenario risk assessment. A cluster analysis based on the k-medoids algorithm is applied to reduce the number of alternatives and identify those which dominate the decision problem. The proposed approach is applied to a system of aging culverts of the German waterways network. Results show that the procedure allows to simplify the analysis and improve communication with infrastructure stakeholders.

Water ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 649 ◽  
Author(s):  
Quansen Wang ◽  
Jianzhong Zhou ◽  
Kangdi Huang ◽  
Ling Dai ◽  
Gang Zha ◽  
...  

The risk inevitably exists in the process of flood control operation and decision-making of reservoir group, due to the hydrologic and hydraulic uncertain factors. In this study different stochastic simulation methods were applied to simulate these uncertainties in multi-reservoir flood control operation, and the risk caused by different uncertainties was evaluated from the mean value, extreme value and discrete degree of reservoir occupied storage capacity under uncertain conditions. In order to solve the conflict between risk assessment indexes and evaluate the comprehensive risk of different reservoirs in flood control operation schemes, the subjective weight and objective weight were used to construct the comprehensive risk assessment index, and the improved Mahalanobis distance TOPSIS method was used to select the optimal flood control operation scheme. The proposed method was applied to the flood control operation system in the mainstream and its tributaries of upper reaches of the Yangtze River basin, and 14 cascade reservoirs were selected as a case study. The results indicate that proposed method can evaluate the risk of multi-reservoir flood control operation from all perspectives and provide a new method for multi-criteria decision-making of reservoir flood control operation, and it breaks the limitation of the traditional risk analysis method which only evaluated by risk rate and cannot evaluate the risk of the multi-reservoir flood control operation system.


2021 ◽  
Vol 13 (6) ◽  
pp. 3133
Author(s):  
Rita Der Sarkissian ◽  
Anas Dabaj ◽  
Youssef Diab ◽  
Marc Vuillet

A limited number of studies in the scientific literature discuss the “Build-Back-Better” (BBB) critical infrastructure (CI) concept. Investigations of its operational aspects and its efficient implementation are even rarer. The term “Better” in BBB is often confusing to practitioners and leads to unclear and non-uniform objectives for guiding accurate decision-making. In an attempt to fill these gaps, this study offers a conceptual analysis of BBB’s operational aspects by examining the term “Better”. In its methodological approach, this study evaluates the state of Saint-Martin’s CI before and after Hurricane Irma and, accordingly, reveals the indicators to assess during reconstruction projects. The proposed methods offer practitioners a guidance tool for planning efficient BBB CI projects or for evaluating ongoing programs through the established BBB evaluation grid. Key findings of the study offer insights and a new conceptual equation of the BBB CI by revealing the holistic and interdisciplinary connotations behind the term “Better” CI: “Build-Back-resilient”, “Build-Back-sustainable”, and “Build-Back-accessible to all and upgraded CI”. The proposed explanations can facilitate the efficient application of BBB for CI by operators, stakeholders, and practitioners and can help them to contextualize the term “Better” with respect to their area and its CI systems.


2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Fateme Omidvari ◽  
Mehdi Jahangiri ◽  
Reza Mehryar ◽  
Moslem Alimohammadlou ◽  
Mojtaba Kamalinia

Fire is one of the most dangerous phenomena causing major casualties and financial losses in hospitals and healthcare settings. In order to prevent and control the fire sources, first risk assessment should be conducted. Failure Mode and Effect Analysis (FMEA) is one of the techniques widely used for risk assessment. However, Risk Priority Number (RPN) in this technique does not take into account the weight of the risk parameters. In addition, indirect relationships between risk parameters and expert opinions are not considered in decision making in this method. The aim is to conduct fire risk assessment of healthcare setting using the application of FMEA combined with Multi‐Criteria Decision Making (MCDM) methods. First, a review of previous studies on fire risk assessment was conducted and existing rules were identified. Then, the factors influencing fire risk were classified according to FMEA criteria. In the next step, weights of fire risk criteria and subcriteria were determined using Intuitionistic Fuzzy Multiplicative Best-Worst Method (IFMBWM) and different wards of the hospital were ranked using Interval-Valued Intuitionistic Fuzzy Combinative Distance-based Assessment (IVIFCODAS) method. Finally, a case study was performed in one of the hospitals of Shiraz University of Medical Sciences. In this study, fire alarm system (0.4995), electrical equipment and installations (0.277), and flammable materials (0.1065) had the highest weight, respectively. The hospital powerhouse also had the highest fire risk, due to the lack of fire extinguishers, alarms and fire detection, facilities located in the basement floor, boilers and explosive sensitivity, insufficient access, and housekeeping. The use of MCDM methods in combination with the FMEA method assesses the risk of fire in hospitals and health centers with great accuracy.


Criminology ◽  
2021 ◽  
Author(s):  
James C. Oleson

The evidence-based practice (EBP) movement can be traced to a 1992 article in the Journal of the American Medical Association, although decision-making with empirical evidence (rather than tradition, anecdote, or intuition) is obviously much older. Neverthless, for the last twenty-five years, EBP has played a pivotal role in criminal justice, particularly within community corrections. While the prediction of recidivism in parole or probation decisions has attracted relatively little attention, the use of risk measures by sentencing judges is controversial. This might be because sentencing typically involves both backward-looking decisions, related to the blameworthiness of the crime, as well as forward-looking decisions, about the offender’s prospective risk of recidivism. Evidence-based sentencing quantifies the predictive aspects of decision-making by incorporating an assessment of risk factors (which increase recidivism risk), protective factors (which reduce recidivism risk), criminogenic needs (impairments that, if addressed, will reduce recidivism risk), the measurement of recidivism risk, and the identification of optimal recidivism-reducing sentencing interventions. Proponents for evidence-based sentencing claim that it can allow judges to “sentence smarter” by using data to distinguish high-risk offenders (who might be imprisoned to mitigate their recidivism risk) from low-risk offenders (who might be released into the community with relatively little danger). This, proponents suggest, can reduce unnecessary incarceration, decrease costs, and enhance community safety. Critics, however, note that risk assessment typically looks beyond criminal conduct, incorporating demographic and socioeconomic variables. Even if a risk factor is facially neutral (e.g., criminal history), it might operate as a proxy for a constitutionally protected category (e.g., race). The same objectionable variables are used widely in presentence reports, but their incorporation into an actuarial risk score has greater potential to obfuscate facts and reify underlying disparities. The evidence-based sentencing literature is dynamic and rapidly evolving, but this bibliography identifies sources that might prove useful. It first outlines the theoretical foundations of traditional (non-evidence-based) sentencing, identifying resources and overviews. It then identifies sources related to decision-making and prediction, risk assessment logic, criminogenic needs, and responsivity. The bibliography then describes and defends evidence-based sentencing, and identifies works on sentencing variables and risk assessment instruments. It then relates evidence-based sentencing to big data and identifies data issues. Several works on constitutional problems are listed, the proxies problem is described, and sources on philosophical issues are described. The bibliography concludes with a description of validation research, the politics of evidence-based sentencing, and the identification of several current initiatives.


2021 ◽  
Author(s):  
Vishal Ahuja ◽  
Carlos A. Alvarez ◽  
John R. Birge ◽  
Chad Syverson

The U.S. Food and Drug Administration (FDA) regulates the approval and safe public use of pharmaceutical products in the United States. The FDA uses postmarket surveillance systems to monitor drugs already on the market; a drug found to be associated with an increased risk of adverse events (ADEs) is subject to a recall or a warning. A flawed postmarket decision-making process can have unintended consequences for patients, create uncertainty among providers and affect their prescribing practices, and subject the FDA to unfavorable public scrutiny. The FDA’s current pharmacovigilance process suffers from several shortcomings (e.g., a high underreporting rate), often resulting in incorrect or untimely decisions. Thus, there is a need for robust, data-driven approaches to support and enhance regulatory decision making in the context of postmarket pharmacovigilance. We propose such an approach that has several appealing features—it employs large, reliable, and relevant longitudinal databases; it uses methods firmly established in literature; and it addresses selection bias and endogeneity concerns. Our approach can be used to both (i) independently validate existing safety concerns relating to a drug, such as those emanating from existing surveillance systems, and (ii) perform a holistic safety assessment by evaluating a drug’s association with other ADEs to which the users may be susceptible. We illustrate the utility of our approach by applying it retrospectively to a highly publicized FDA black box warning (BBW) for rosiglitazone, a diabetes drug. Using comprehensive data from the Veterans Health Administration on more than 320,000 diabetes patients over an eight-year period, we find that the drug was not associated with the two ADEs that led to the BBW, a conclusion that the FDA evidently reached, as it retracted the warning six years after issuing it. We demonstrate the generalizability of our approach by retroactively evaluating two additional warnings, those related to statins and atenolol, which we found to be valid. This paper was accepted by Vishal Gaur, operations management.


Risk Analysis ◽  
1991 ◽  
pp. 655-665
Author(s):  
S. P. Proctor ◽  
G. Marchant ◽  
M. S. Baram

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