Correlation of Quantitative Risk Results for High Hazard Processes

A quantitative risk analysis was conducted to evaluate the design of the VX neutralization subsystem and related support facilities of the U.S. Army Newport Chemical Agent Disposal Facility. Three major incidents including agent release, personnel injury, and system loss were studied using fault tree analysis methodology. Each incident was assigned a risk assessment code based on the severity level and probability of occurrence of the incident. Safety mitigations or design changes were recommended to bring the "undesired" risk level (typical agent release events) to be "acceptable with controls" or "acceptable."     

Reconfiguring the Supply Network Using Current Performance Data

Reconfiguration of the supply chain network from time to time is essential for businesses to retain their competitive edge. This paper presents a methodology for reconfiguration of an existing supply chain network. The methodology is characterized by two decision levels. In the first level, the current network performance is evaluated and efficient practices are identified. In the next level, a model that incorporates efficient practices is developed to reconfigure the network. This integrated methodology allows for decision maker (DM) input throughout the process. The methodology has been implemented and tested in the reconfiguration of an outbound petroleum supply chain network for CountryMark Cooperative, Inc. In this case study, Data Envelopment Analysis (DEA) is used to analyze current operations and an integer programming (IP) model that incorporates efficiency metrics is developed for selection of distribution facilities and allocation of resources to the facilities. Use of this methodology can lead to improved operations and reduced operating expenses.     

Book reviews

This paper is aimed at developing and testing a methodology to evaluate the most appropriate collaboration level within a given supply chain. In particular, the proposed methodology is conceived for logistic networks belonging to the consumer packaged goods industry, e.g. the grocery industry, and it consists of: (i) identifying an approximation of collaboration, (ii) representing through such approximation the different options among collaborative planning forecasting and replenishment (CPFR), vendor management inventory (VMI) and loosely collaborative approach (LCA); (iii) using a simulation-based decision support system to select the best collaboration level. The proposed methodology has been applied to a real-life supply chain in the food and beverage industry. Results conclude that the methodology proposed here proved useful in facing the problem of collaboration level definition among the nodes of a consumer packaged goods logistic network.     

Pathway Analysis for Population-Total Health Impacts of Toxic Metal Emissions

This article describes a simple model for quantifying the health impacts of toxic metal emissions. In contrast to most traditional models it calculates the expectation value of the total damage (summed over the total population and over all time) for typical emission sites, rather than "worst-case" estimates for specific sites or episodes. Such a model is needed for the evaluation of many environmental policy measures, e.g., the optimal level of pollution taxes or emission limits. Based on the methodology that has been developed by USEPA for the assessment of multimedia pathways, the equations and parameters are assembled for the assessment of As, Cd, Cr, Hg, Ni, and Pb, and some typical results are presented (the dose from seafood is not included and for Hg the results are extremely uncertain); the model is freely available on the web. The structure of the model is very simple because, as we show, if the parameters can be approximated by time-independent constants (the case for the USEPA methodology), the total impacts can be calculated with steady-state models even though the environment is never in steady state. The collective ingestion dose is found to be roughly 2 orders of magnitude larger than the collective dose via inhalation. The uncertainties are large, easily an order of magnitude, the main uncertainties arising from the parameter values of the model, in particular the transfer factors. Using linearized dose-response functions, estimates are provided for cancers due to As, Cd, Cr, and Ni as well as IQ loss due to Pb emissions in Europe.     

Multiobjective Risk-Impact Analysis Method

This paper integrates two methodologies of risk and impact analysis—the partitioned multiobjective risk method (PMRM) and the multiobjective, multistage impact analysis method (MMIAM). The PMRM, in an effort to overcome the difficulties created by commensurating extreme events that have catastrophic impacts with those that have more frequent but less harmful consequences, introduces the use of conditional expectations for different regimes of probabilities and damages. The MMIAM is a multiobjective decisionmaking method for impact analysis which explicitly develops trade-offs among different objectives at different stages or periods. Decision makers who must act under conditions of extreme risk and uncertainty often find that they are more interested in knowing "what not to do" than they are in optimizing their current objectives (the more traditional aim of decision-making methodologies). This paper focuses on a way to answer their needs, in which major elements of both the PMRM and the MMIAM are combined in a new, integrated methodology, termed here the multiobjective risk-impact analysis method (MRIAM). The new methodology incorporates risk and impact analysis within a dynamic multiobjective decision-making framework. To demonstrate the usefulness of the integrated methodology, an example problem concerning the environmental effects of pollutant emissions over a number of years is formulated, solved, and analyzed.     

An ALARA Approach to the Radiological Control of Foodstuffs Following an Accidental Release

This article presents a methodology based on two complementary approaches, thus allowing a selection of maximal concentration in foodstuffs for determining appropriate countermeasures. The first approach is based on a minimal and maximal per capita intervention level and takes into account the annual intake of each product. The second one is based on a cost-benefit analysis, comparing the advantages of a countermeasure concerning those products presenting a contamination higher than a given maximal concentration (in terms of reduction of cost of the detriment associated with the risk), with its drawbacks (in terms of cost of the products) in order to select the "ALARA" maximal concentration. This second approach is used as a complement to the first one. The results obtained through these two approaches are given for four products (milk, meat, fresh vegetables, and corn) and two nuclides (Cs-137 and I-131). These are presented for various scenarios: one or various products contaminated by one or various radionuclides. It is concluded that these two approaches are complementary, the first one being related to individual risk and the second to collective risk. Therefore, these approaches are both of interest in the context of the elaboration of modalities for the radiological control of foodstuffs following an accidental release and both methods may be useful for determining appropriate countermeasures.     

A guide for supply chain integration in SMEs

Supply chain integration (SCI) is a competitive business approach for enterprises that has not been implemented as widely as expected in small and medium-sized enterprises (SMEs). One of the factors explaining this low level of application is the lack of methodologies to develop SCI that fit the characteristics of this type of enterprise. In this article, we present a methodology that enables SMEs to achieve correct SCI in a manner that is simple, straightforward and oriented towards their particular characteristics. Thus, SMEs will be able to align and coordinate the aims, resources, decisions, methods, business processes and employees involved in the supply chain. The methodology addresses the problem of SMEs SCI and it was produced by applying the case study research method to 30 industrial SMEs. The methodology is organised in phases and the activities to be performed, the techniques and supporting tools to be used, as well as the expected outcomes are all described for each phase. With this methodology, it becomes possible to overcome the main barriers that prevent SMEs from achieving a correct integration of their supply chains. In addition to the methodology, this article also outlines the significant benefits observed in the 30 enterprises as a result of its application.     

Bounding Analysis as an Inadequately Specified Methodology

The bounding analysis methodology described by Ha-Duong et al. (this issue) is logically incomplete and invites serious misuse and misinterpretation, as their own example and interpretation illustrate. A key issue is the extent to which these problems are inherent in their methodology, and resolvable by a logically complete assessment (such as Monte Carlo or Bayesian risk assessment), as opposed to being general problems in any risk-assessment methodology. I here attempt to apportion the problems between those inherent in the proposed bounding analysis and those that are more general, such as reliance on questionable expert elicitations. I conclude that the specific methodology of Ha-Duong et al. suffers from logical gaps in the definition and construction of inputs, and hence should not be used in the form proposed. Furthermore, the labor required to do a sound bounding analysis is great enough so that one may as well skip that analysis and carry out a more logically complete probabilistic analysis, one that will better inform the consumer of the appropriate level uncertainty. If analysts insist on carrying out a bounding analysis in place of more thorough assessments, extensive analyses of sensitivity to inputs and assumptions will be essential to display uncertainties, arguably more essential than it would be in full probabilistic analyses.     

A robust ranking method extending ELECTRE III to hierarchy of interacting criteria,imprecise weights and stochastic analysis

A great majority of methods designed for Multiple Criteria Decision Aiding (MCDA) assume that all assessment criteria are considered at the same level, however, decision problems encountered in practice often impose a hierarchical structure of criteria. The hierarchy helps to decompose complex decision problems into smaller and manageable subtasks, and thus, it is very attractive for computational efficiency and explanatory purposes. To handle the hierarchy of criteria in MCDA, a methodology called Multiple Criteria Hierarchy Process (MCHP), has been recently proposed. MCHP permits to consider preference relations with respect to a subset of criteria at any level of the hierarchy. Here, we propose to apply MCHP to the ELECTRE III ranking method adapted to handle three types of interaction effects between criteria: mutual-weakening, mutual-strengthening and antagonistic effect. We also involve in MCHP an imprecise elicitation of criteria weights, generalizing a technique called the SRF method. In order to explore the plurality of rankings obtained by the ELECTRE III method for possible sets of criteria weights, we apply the Stochastic Multiobjective Acceptability Analysis (SMAA) that permits to draw robust conclusions in terms of rankings and preference relations at each level of the hierarchy of criteria. The novelty of the whole methodology consists of a joint consideration of hierarchical assessments of alternatives performances on interacting criteria, imprecise criteria weights, and robust analysis of ranking recommendations resulting from ELECTRE III. An example regarding the multiple criteria ranking of some European universities will show how to apply the proposed methodology on a decision problem.     

Stochastic Response Surface Methods (SRSMs) for Uncertainty Propagation: Application to Environmental and Biological Systems

Comprehensive uncertainty analyses of complex models of environmental and biological systems are essential but often not feasible due to the computational resources they require. "Traditional" methods, such as standard Monte Carlo and Latin Hypercube Sampling, for propagating uncertainty and developing probability densities of model outputs, may in fact require performing a prohibitive number of model simulations. An alternative is offered, for a wide range of problems, by the computationally efficient "Stochastic Response Surface Methods (SRSMs)" for uncertainty propagation. These methods extend the classical response surface methodology to systems with stochastic inputs and outputs. This is accomplished by approximating both inputs and outputs of the uncertain system through stochastic series of "well behaved" standard random variables; the series expansions of the outputs contain unknown coefficients which are calculated by a method that uses the results of a limited number of model simulations. Two case studies are presented here involving (a) a physiologically-based pharmacokinetic (PBPK) model for perchloroethylene (PERC) for humans, and (b) an atmospheric photochemical model, the Reactive Plume Model (RPM-IV). The results obtained agree closely with those of traditional Monte Carlo and Latin Hypercube Sampling methods, while significantly reducing the required number of model simulations.     

能源强度的指数分解分析研究综述

指数分解分析是一个研究能源强度变化及其作用机理的良好分析框架,围绕这一方法,综述了指数分解分析在方法论方面的研究现状及其在能源领域,尤其在能源强度方面的应用研究。将我国学者关于能源强度变化的研究结论划分为3类:技术进步决定论、阶段贡献变化论和分解层次影响论,并指出了指数分解分析在研究能源强度变化机理中的三大缺陷。最后,对未来的研究方向进行了展望。     

期货保证金调整对中国钢材市场价格发现的影响研究

近年来,上海期货交易所频繁调整大宗商品期货的交易保证金,以期抑制市场风险。这种调整措施给中国钢材市场的价格发现过程究竟会带来何种影响,是理论界和实践界关注的问题。本文针对上海期货交易所于2010年11月29日上调钢材期货保证金比例和2012年5月2日下调保证金比例这两项措施,采用基于VECM模型的信息份额方法,定量测算了中国三类钢材市场对钢材价格发现过程的贡献。研究结果表明,调升期货保证金的措施可抑制钢材市场价格波动风险、提升期货市场的价格发现功能;调降期货保证金后,期货市场对价格发现过程的贡献度仍占1/3以上;电子交易市场价格发现功能受期货保证金调整影响较大。在钢材期货价格剧烈波动时,电子交易市场作为价格发现工具能引导其它两类市场价格。     

A COMPARISON OF PRODUCTION SCHEDULING POLICIES ON COSTS,SERVICE LEVEL,AND SCHEDULE CHANGES

We consider a single product, single level, stochastic master production scheduling (Mps ) model where decisions are made under rolling planning horizons. Outcomes of interest are cost, service level, and schedule stability. The subject of this research is the Mps control system: the method used in determining the amount of stock planned for production in each time period. Typically, Mps control systems utilize a single buffer stock. Here, two Mps dual-buffer stock systems are developed and tested by simulation. We extend the data envelopment analysis (dea ) methodology to aid in the evaluation of the simulation results, where Dea serves to increase the scope of the experimental design. Results indicate that the dual-buffer control systems outperform existing policies.     

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.     

交叉上市股票价格发现能力差异及交易信息含量测度

本文在市场微观结构的理论框架下,对交叉上市股票的价格发现过程进行了分析。在Hasbrouck信息分成技术的基础上,提供了一种新的方法使其能够对市场交易过程中的公开信息和私有信息含量进行分解和测度。研究过程以 "A+H"交叉上市股票为研究对象,对本文的模型和方法进行了具体的应用和验证。     

A multiple goal methodology for evaluating management information systems

The behavior and performance of an organization are intimately tied to the mode and effectiveness of its information processing function. While there is a rapidly expanding level of research concerned with the design, development, and implementation of management information systems (MIS), relatively few approaches to the evaluation and improvement of these systems have been suggested. The current paper develops a multiple goal methodology aimed at filling this gap by evaluating and, if necessary, subsequently modifying any given set of MIS design variables considered capable of enhancing a series of operational and, perhaps, conflicting goals. The methodology is based on a series of significant findings from the MIS design literature. In particular, the procedure incorporates the tripartite of decision type/decision-maker/MIS design into the evaluation process. The methodology is user-based, being flexible with respect to the definition of performance objectives, evaluation measures, design variables, and correction strategies. A brief example applies the methodology to the evaluation of an MIS within a health services organization.     

Assessing the Benefits and Costs of Homeland Security Research: A Risk-Informed Methodology with Applications for the U.S. Coast Guard

This article describes a methodology for risk-informed benefit–cost analyses of homeland security research products. The methodology is field-tested with 10 research products developed for the U.S. Coast Guard. Risk-informed benefit–cost analysis is a tool for risk management that integrates elements of risk analysis, decision analysis, and benefit–cost analysis. The cost analysis methodology includes a full-cost accounting of research projects, starting with initial fundamental research costs and extending to the costs of implementation of the research products and, where applicable, training, maintenance, and upgrade costs. The benefits analysis methodology is driven by changes in costs and risks leading to five alternative models: cost savings at the same level of security, increased security at the same cost, signal detection improvements, risk reduction by deterrence, and value of information. The U.S. Coast Guard staff selected 10 research projects to test and generalize the methodology. Examples include tools to improve the detection of explosives, reduce the costs of harbor patrols, and provide better predictions of hurricane wind speeds and floods. Benefits models and estimates varied by research project and many input parameters of the benefit estimates were highly uncertain, so risk analysis for sensitivity testing and simulation was important. Aggregating across the 10 research products, we found an overall median net present value of about $385 million, with a range from $54 million (5th percentile) to $877 million (95th percentile). Lessons learned are provided for future applications.     

Hybrid Processing of Stochastic and Subjective Uncertainty Data

Uncertainty analyses typically recognize separate stochastic and subjective sources of uncertainty, but do not systematically combine the two, although a large amount of data used in analyses is partly stochastic and partly subjective. We have developed methodology for mathematically combining stochastic and subjective sources of data uncertainty, based on new "hybrid number" approaches. The methodology can be utilized in conjunction with various traditional techniques, such as PRA (probabilistic risk assessment) and risk analysis decision support. Hybrid numbers have been previously examined as a potential method to represent combinations of stochastic and subjective information, but mathematical processing has been impeded by the requirements inherent in the structure of the numbers, e.g., there was no known way to multiply hybrids. In this paper, we will demonstrate methods for calculating with hybrid numbers that avoid the difficulties. By formulating a hybrid number as a probability distribution that is only fuzzily known, or alternatively as a random distribution of fuzzy numbers, methods are demonstrated for the full suite of arithmetic operations, permitting complex mathematical calculations. It will be shown how information about relative subjectivity (the ratio of subjective to stochastic knowledge about a particular datum) can be incorporated. Techniques are also developed for conveying uncertainty information visually, so that the stochastic and subjective components of the uncertainty, as well as the ratio of knowledge about the two, are readily apparent. The techniques demonstrated have the capability to process uncertainty information for independent, uncorrelated data, and for some types of dependent and correlated data. Example applications are suggested, illustrative problems are shown, and graphical results are given.     

Estimation of Potential Health Effects from Acute Exposure to Hydrogen Fluoride Using a "Benchmark Dose" Approach

Communities across the United States are examining the manufacture, use, transport, and storage of hydrogen fluoride (HF) near residential areas as a consequence of a major release of HF in Texas in 1987. Reference exposure levels for routine and accidental HF emissions are calculated using existing animal and human data. The approach employs a logprobit extrapolation of concentration-response data to the 95% lower confidence limit on the toxic concentration producing a "benchmark dose" of 1% response (TC01), called a practical threshold. Species-specific and chemical-specific adjustment factors are applied to develop exposure levels applicable to the general public. Using this method, the 1-hr reference exposure level to protect the public against any irritation from a routine emission (REL-1) is 0.7 ppm and the level to protect against severe irritation from a once-in-a-lifetime (REL-2) release is 2 ppm. This approach is compared to a modified "uncertainty factor" approach.