On The Quantitative Definition of Risk

A quantitative definition of risk is suggested in terms of the idea of a "set of triplets". The definition is extended to include uncertainty and completeness, and the use of Bayes' theorem is described in this connection. The definition is used to discuss the notions of "relative risk", "relativity of risk", and "acceptability of risk".     

Estimation of Long-Term Risk from Canadian Uranium Mill Tailings

A methodology is presented for assessing the risk from Canadian uranium mill tailings piles. The methodology is based on the "set of triplets" concept and uses an event tree to identify various scenarios representing the performance of a pile over its 1,000-year design life. Compartment-type mathematical models are used to quantify the movement of hazardous substances through the environment. Numerical examples are given of both "level 1" (straight probabilistic) and "level 2" (probability of frequency) type analyses.     

Risk filtering, ranking, and management framework using hierarchical holographic modeling.

This paper contributes a methodological framework to identify, prioritize, assess, and manage risk scenarios of a large-scale system. Qualitative screening of scenarios and classes of scenarios is appropriate initially, while quantitative assessments may be applied once the set of all scenarios (hundreds) has been prioritized in several phases. The eight-phase methodology is described in detail and is applied to operations other than war. The eight phases are as follows: Phase I, Scenario Identification-A hierarchical holographic model (HHM) is developed to describe the system's "as planned" or "success" scenario. Phase II, Scenario Filtering-The risk scenarios identified in Phase I are filtered according to the responsibilities and interests of the current system user. Phase III, Bi-Criteria Filtering and Ranking. Phase IV, Multi-Criteria Evaluation. Phase V, Quantitative Ranking-We continue to filter and rank scenarios based on quantitative and qualitative matrix scales of likelihood and consequence; and ordinal response to system resiliency, robustness, redundancy. Phase VI, Risk Management is performed, involving identification of management options for dealing with the filtered scenarios, and estimating the cost, performance benefits, and risk reduction of each. Phase VII, Safeguarding Against Missing Critical Items--We examine the performance of the options selected in Phase VI against the scenarios previously filtered out during Phases II to V. Phase VIII, Operational Feedback-We use the experience and information gained during application to refine the scenario filtering and decision processes in earlier phases. These eight phases reflect a philosophical approach rather than a mechanical methodology. In this philosophy, the filtering and ranking of discrete scenarios is viewed as a precursor to, rather than a substitute for, consideration of the totality of all risk scenarios.     

A Systems‐Based Risk Assessment Framework for Intentional Electromagnetic Interference (IEMI) on Critical Infrastructures

Modern infrastructures are becoming increasingly dependent on electronic systems, leaving them more vulnerable to electrical surges or electromagnetic interference. Electromagnetic disturbances appear in nature, e.g., lightning and solar wind; however, they may also be generated by man‐made technology to maliciously damage or disturb electronic equipment. This article presents a systematic risk assessment framework for identifying possible, consequential, and plausible intentional electromagnetic interference (IEMI) attacks on an arbitrary distribution network infrastructure. In the absence of available data on IEMI occurrences, we find that a systems‐based risk assessment is more useful than a probabilistic approach. We therefore modify the often applied definition of risk, i.e., a set of triplets containing scenario, probability, and consequence, to a set of quadruplets: scenario, resource requirements, plausibility, and consequence. Probability is “replaced” by resource requirements and plausibility, where the former is the minimum amount and type of equipment necessary to successfully carry out an attack scenario and the latter is a subjective assessment of the extent of the existence of attackers who possess the motivation, knowledge, and resources necessary to carry out the scenario. We apply the concept of intrusion areas and classify electromagnetic source technology according to key attributes. Worst‐case scenarios are identified for different quantities of attacker resources. The most plausible and consequential of these are deemed the most important scenarios and should provide useful decision support in a countermeasures effort. Finally, an example of the proposed risk assessment framework, based on notional data, is provided on a hypothetical water distribution network.     

Variations in Concepts of "Susceptibility" in Risk Assessment

The Food Quality Protection Act and the 1996 amendments to the Safe Drinking Water Act are two of the most recent examples of legislation calling for protection of susceptible subpopulations. As regulatory deadlines draw nearer, controversies in scientific and policy arenas increase about incorporating susceptibility in risk assessment. The previously accepted working definition of "susceptibility" has already been called into question. Part of the controversy results from different disciplines conceiving of susceptibility in different ways. Understanding the conceptual differences embodied within definitions can provide a basis on which a revised working definition may be developed across disciplines. The purposes of this article are to describe the varying definitions of susceptibility, discuss the differing concepts incorporated in the definitions, and recommend ways in which susceptibility may be defined and framed to meet current risk assessment needs. The present analysis of definitions from the fields of ecology, biology, engineering, medicine, epidemiology, and toxicology revealed different emphases that relate to the underlying perspectives and methods of each field. It is likely that susceptibility will need to be formally defined for public policy purposes, but until that time, the use of more informal communication and decision-making processes is suggested to develop and utilize a new working consensus on the definition of susceptibility.     

Quantitative Risk Assessment of the New York State Operated West Valley Radioactive Waste Disposal Area

This article is based on a quantitative risk assessment (QRA) that was performed on a radioactive waste disposal area within the Western New York Nuclear Service Center in western New York State. The QRA results were instrumental in the decision by the New York State Energy Research and Development Authority to support a strategy of in‐place management of the disposal area for another decade. The QRA methodology adopted for this first of a kind application was a scenario‐based approach in the framework of the triplet definition of risk (scenarios, likelihoods, consequences). The measure of risk is the frequency of occurrence of different levels of radiation dose to humans at prescribed locations. The risk from each scenario is determined by (1) the frequency of disruptive events or natural processes that cause a release of radioactive materials from the disposal area; (2) the physical form, quantity, and radionuclide content of the material that is released during each scenario; (3) distribution, dilution, and deposition of the released materials throughout the environment surrounding the disposal area; and (4) public exposure to the distributed material and the accumulated radiation dose from that exposure. The risks of the individual scenarios are assembled into a representation of the risk from the disposal area. In addition to quantifying the total risk to the public, the analysis ranks the importance of each contributing scenario, which facilitates taking corrective actions and implementing effective risk management. Perhaps most importantly, quantification of the uncertainties is an intrinsic part of the risk results. This approach to safety analysis has demonstrated many advantages of applying QRA principles to assessing the risk of facilities involving hazardous materials.     

A multiobjective model and evolutionary algorithms for robust time and space assembly line balancing under uncertain demand

Changes in demand when manufacturing different products require an optimization model that includes robustness in its definition and methods to deal with it. In this work we propose the r-TSALBP, a multiobjective model for assembly line balancing to search for the most robust line configurations when demand changes. The robust model definition considers a set of demand scenarios and presents temporal and spatial overloads of the stations in the assembly line of the products to be assembled. We present two multiobjective evolutionary algorithms to deal with one of the r-TSALBP variants. The first algorithm uses an additional objective to evaluate the robustness of the solutions. The second algorithm employs a novel adaptive method to evolve separate populations of robust and non-robust solutions during the search. Results show the improvements of using robustness information during the search and the outstanding behavior of the adaptive evolutionary algorithm for solving the problem. Finally, we analyze the managerial impacts of considering the r-TSALBP model for the different organization departments by exploiting the values of the robustness metrics.     

具有遗憾值约束的鲁棒供应链网络设计模型研究

考虑不确定性环境,研究战略层次的供应链网络鲁棒设计问题,目标是设计参数发生摄动时,供应链性能能够保持稳健性。基于鲁棒解的定义,建立从上游供应商选择到下游设施选址-需求分配的供应链网络设计鲁棒优化模型;提出确定遗憾值限定系数上限和下限的方法,允许决策者调节鲁棒水平,选择多种供应链网络结构;通过模型分解与协调,设计了供应链节点配置的禁忌搜索算法。算例的计算结果表明了禁忌搜索算法具有良好的收敛特性,以及在处理大规模问题上的优越性;同时也反映了利用鲁棒优化模型进行供应链网络设计,可以有效规避投资风险。     

Is Epidemiology the Key to Cumulative Risk Assessment?

Although cumulative risk assessment by definition evaluates the joint effects of chemical and nonchemical stressors, studies to date have not considered both dimensions, in part because toxicological studies cannot capture many stressors of interest. Epidemiology can potentially include all relevant stressors, but developing and extracting the necessary information is challenging given some of the inherent limitations of epidemiology. In this article, I propose a conceptual framework within which epidemiological studies could be evaluated for their inclusion into cumulative risk assessment, including a problem formulation/planning and scoping step that focuses on stressors meaningful for risk management decisions, extension of the chemical mixtures framework to include nonchemical stressors, and formal consideration of vulnerability characteristics of the population. In the long term, broadening the applicability and informativeness of cumulative risk assessment will require enhanced communication and collaboration between epidemiologists and risk assessors, in which the structure of social and environmental epidemiological analyses may be informed in part by the needs of cumulative risk assessment.     

Selection of supply portfolio under disruption risks

This paper deals with the optimal selection of supply portfolio in a make-to-order environment in the presence of supply chain disruption risks. Given a set of customer orders for products, the decision maker needs to decide from which supplier to purchase custom parts required for each customer order to minimize total cost and mitigate the impact of disruption risks. The selection of suppliers and allocation of orders is based on price and quality of purchased parts and reliability of delivery. The two types of disruption scenarios are considered: scenarios with independent local disruptions of each supplier and scenarios with local and global disruptions that may result in all suppliers disruption simultaneously. The problem is formulated as a single- or bi-objective mixed integer program and a value-at-risk and conditional value-at-risk approach is applied to control the risk of supply disruptions. The proposed portfolio approach is capable of optimizing the supply portfolio by calculating value-at-risk of cost per part and minimizing expected worst-case cost per part simultaneously. Numerical examples are presented and some computational results are reported.     

Scenario-Based Risk Assessment of Multi-Use Chemicals: Application to Solvents

The risk through chemical exposure is commonly characterized by ratios of exposure concentrations and effect levels (risk quotients). For chemicals with many different applications such as solvents, however, in addition to the risk quotients of different exposure situations it is useful to determine the corresponding numbers of exposed individuals, that is, not only the magnitude but also the extent of the risk. To this end, the Scenario-Based Risk Assessment (SceBRA) method has been developed that makes use of a large set of scenarios, each of which describes a typical situation regarding handling a solvent or solvent-containing product. The scenarios cover the life-cycle steps of production, distribution, and use of solvents. For each scenario, SceBRA provides the risk quotient, r, and the number of exposed individuals, N. This study investigated seven solvents that are used in large amounts in Switzerland. For each solvent, characteristic distributions of r and N values were calculated, making it possible to compare different solvents with respect to their risk profile. Graphical representations of the r, N data provide an informative way for analyzing and communicating the results of SceBRA.     

A Scale of Risk

This article proposes a conceptual framework for ranking the relative gravity of diverse risks. This framework identifies the moral considerations that should inform the evaluation and comparison of diverse risks. A common definition of risk includes two dimensions: the probability of occurrence and the associated consequences of a set of hazardous scenarios. This article first expands this definition to include a third dimension: the source of a risk. The source of a risk refers to the agents involved in the creation or maintenance of a risk and captures a central moral concern about risks. Then, a scale of risk is proposed to categorize risks along a multidimensional ranking, based on a comparative evaluation of the consequences, probability, and source of a given risk. A risk is ranked higher on the scale the larger the consequences, the greater the probability, and the more morally culpable the source. The information from the proposed comparative evaluation of risks can inform the selection of priorities for risk mitigation.     

The Phenomenology of Earnings Management within the Confines of Agency Theory

Agents' selective and acceptable reporting of economic events by different accounting systems, compounded by alternative accounting methods and estimates, make financial statements an approximation of economic reality. The tendency to delay accounting recognition of some transactions suggests that financial statements lag behind reality. The difference between reality and imaginary is often referred to as the agency problem. An essential characteristic of this problem is risk attitudes of principals (shareholders) and agents (management). Shareholders are considered risk neutral in their preferences for individual firms. They are in a position to diversify their shareholdings across multiple firms. Agents on the other hand have security and income that are inextricably linked to one firm. It would not be surprising to find agents exhibiting risk aversion in decisions regarding the firm. Immediately one's attention is drawn to the opportunity costs that arise for the risk-neutral shareholders who prefer that agents maximize their returns. The risk differential between agents and principals creates a problem in principal-agent relationship. It is within this framework that supervisory and incentive alignment mechanisms that alter the risk orientation of agents are set up. Powerful incentives act upon agents as they exercise their judgment, particularly when the judgment can trigger a stock market response that will, in turn, affect the firm in numerous ways. The responsibility of agents is to manage earnings. From a principal's perspective not all of the methods used to achieve this goal are equally desirable. Agents can either increase productivity or they can strategically manipulate accounting choices to affect earnings. The latter method need not come with any associated changes in productivity. Consequently, there is misstatement of the financial results and position. The calculus of earnings management is considered within the confines of agents' treatment of risk. Using an Agency Theory framework, this study examines the techniques used by agents to manage and manipulate earnings. The study initially tests the hypothesis whether earnings are really managed. For this purpose two manipulation indices were developed and based upon these indices the phenomenology earnings management was considered.     

考虑多种诱导信息下公众满意度的舆情危机响应决策方法

针对当前研究较少考虑到多种诱导信息情境下舆情危机响应决策问题的现状,首先在介绍研究理论和方法的基础上,对该决策问题进行了描述;然后,通过分析诱导信息的属性结构及其量化方式,运用前景理论从属性层面,提出了舆情危机特定情景和响应方案下公众对多种诱导信息发展态势满意度的计算方法;进一步地,考虑到方案对危机情景演变的影响,运用累积前景理论从公众满意度干预视角,提出了方案筛选的风险决策方法。最后,以一类重大传染病疫情场景中舆情危机响应决策问题为例,介绍该方法的潜在应用和说明其有效性。     

基于HHM-RFRM的船舶航行风险评估方法研究

船舶航行风险是由各种风险因素交互作用产生。综合 HHM-RFRM 理论，构建船舶航行多维风险情景危险度测度模型，以风险因素耦合视角探讨船舶航行风险管理问题。在船舶航行多维风险情景危险度测度模型中结合贝叶斯定理，对船舶航行风险情景进行了定性与定量化过滤、评级。最后以大连港某从事商务活动的货船为例，验证了所提出方法的可行性。传统的风险评估方法只能评估单个风险因素对系统的影响，此评估方法克服了这一局限性，为船舶航行风险管理提供新的视角。     

Model uncertainty and choices made by modelers: lessons learned from the International Atomic Energy Agency model intercomparisons.

The treatment of uncertainties associated with modeling and risk assessment has recently attracted significant attention. The methodology and guidance for dealing with parameter uncertainty have been fairly well developed and quantitative tools such as Monte Carlo modeling are often recommended. However, the issue of model uncertainty is still rarely addressed in practical applications of risk assessment. The use of several alternative models to derive a range of model outputs or risks is one of a few available techniques. This article addresses the often-overlooked issue of what we call "modeler uncertainty," i.e., difference in problem formulation, model implementation, and parameter selection originating from subjective interpretation of the problem at hand. This study uses results from the Fruit Working Group, which was created under the International Atomic Energy Agency (IAEA) BIOMASS program (BIOsphere Modeling and ASSessment). Model-model and model-data intercomparisons reviewed in this study were conducted by the working group for a total of three different scenarios. The greatest uncertainty was found to result from modelers' interpretation of scenarios and approximations made by modelers. In scenarios that were unclear for modelers, the initial differences in model predictions were as high as seven orders of magnitude. Only after several meetings and discussions about specific assumptions did the differences in predictions by various models merge. Our study shows that parameter uncertainty (as evaluated by a probabilistic Monte Carlo assessment) may have contributed over one order of magnitude to the overall modeling uncertainty. The final model predictions ranged between one and three orders of magnitude, depending on the specific scenario. This study illustrates the importance of problem formulation and implementation of an analytic-deliberative process in risk characterization.     

面向双层自动分拣系统的包裹分拣优化模型与算法研究

近年来随着电子商务的快速发展,分拣订单呈现批量小、品种多、配送周期短、精度要求高等特征,这对分拣作业提出了更高的要求。为了缩短分拣时间、降低分拣成本、提高分拣效率,物流企业开始逐步使用双层分拣设备。本文采用了"成组分拣"方法以提升托盘利用率,"成组分拣"是指一种将分散的单件包裹按一定的规则组合在一起,成为一个规格化、标准化的大分拣单元进行分拣的方法。根据"成组分拣"的定义,本文研究了一个考虑成组分拣的双层分拣设备目的地指派问题,并设计了一种高效的变邻域禁忌搜索算法,该算法能在较短时间内对该问题进行求解,得到一个满意解。实验结果表明,采用"成组分拣"方法与考虑目的地指派问题可有效提高分拣设备的分拣效率。     

Plurality of Worlds, Plurality of Risks

Risk management decisions are not made only on the basis of expert risk assessment. In numerous instances, public controversy erupts, questioning the results of previous risk assessment procedures and shaping the development of risk management episodes. This article presents a case study of risk management in the context of a 1980s controversy over aerial spraying against a spruce budworm epidemic in Quebec and draws some general conclusions concerning the relationship between risk analysis and public controversies. Actors in public controversies define risks more broadly than risk assessment experts. Moreover, public controversies only partly concern issues of risk. They are first and foremost debates about social choices in which actors carry with them a multidimensional social experience of technology, trust, credibility and decision-making institutions. This experience contributes to the construction of a plurality of emergent representations of what is at stake in a controversy, referred to in this paper as "worlds of relevance." Analysis shows that in any given public controversy, there are not just two parties arguing against each other. Rather, several "worlds of relevance" can be found that link, in a variety of ways, a variety of entities not necessarily shared by all these worlds. Each "world of relevance" presents a different definition of what the issues and the stakes of the controversy are. Risks are only part of the picture, and they are embedded in "worlds of relevance" from which they take their significance. The successful management of a controversy entails the association of entities from different worlds.     

Scenario Discovery with Multiple Criteria: An Evaluation of the Robust Decision‐Making Framework for Climate Change Adaptation

There is increasing concern over deep uncertainty in the risk analysis field as probabilistic models of uncertainty cannot always be confidently determined or agreed upon for many of our most pressing contemporary risk challenges. This is particularly true in the climate change adaptation field, and has prompted the development of a number of frameworks aiming to characterize system vulnerabilities and identify robust alternatives. One such methodology is robust decision making (RDM), which uses simulation models to assess how strategies perform over many plausible conditions and then identifies and characterizes those where the strategy fails in a process termed scenario discovery. While many of the problems to which RDM has been applied are characterized by multiple objectives, research to date has provided little insight into how treatment of multiple criteria impacts the failure scenarios identified. In this research, we compare different methods for incorporating multiple objectives into the scenario discovery process to evaluate how they impact the resulting failure scenarios. We use the Lake Tana basin in Ethiopia as a case study, where climatic and environmental uncertainties could impact multiple planned water infrastructure projects, and find that failure scenarios may vary depending on the method used to aggregate multiple criteria. Common methods used to convert multiple attributes into a single utility score can obscure connections between failure scenarios and system performance, limiting the information provided to support decision making. Applying scenario discovery over each performance metric separately provides more nuanced information regarding the relative sensitivity of the objectives to different uncertain parameters, leading to clearer insights on measures that could be taken to improve system robustness and areas where additional research might prove useful.