Preventing the Importation of Illicit Nuclear Materials in Shipping Containers

We develop a mathematical model to find the optimal inspection strategy for detecting a nuclear weapon (or nuclear material to make a weapon) from being smuggled into the United States in a shipping container, subject to constraints of port congestion and an overall budget. We consider an 11-layer security system consisting of shipper certification, container seals, and a targeting software system, followed by passive (neutron and gamma), active (gamma radiography), and manual testing at overseas and domestic ports. Currently implemented policies achieve a low detection probability, and improved security requires passive and active testing of trusted containers and manually opening containers that cannot be penetrated by radiography. The annual cost of achieving a high detection probability of a plutonium weapon using existing equipment in traditional ways is roughly several billion dollars if testing is done domestically, and is approximately five times higher if testing is performed overseas. Our results suggest that employing high-energy x-ray radiography and elongating the passive neutron tests at overseas ports may provide significant cost savings, and several developing technologies, radiation sensors inside containers and tamper-resistant electronic seals, should be pursued aggressively. Further effort is critically needed to develop a practical neutron interrogation scheme that reliably detects moderately shielded, highly enriched uranium.     

社会系统多元情景可计算模式研究

鉴于社会系统主体的适应性、结构的涌现性及演化路径的多样性,需要从情景着手来更好地研究社会系统.首先基于复杂科学视角,界定社会系统情景的深刻内涵;其次,分析社会系统情景可计算性的三层结构模型;第三,构建从实际情景到概念情景、从概念情景到结构化情景、从结构化情景到计算机实现的社会系统多元情景近似可计算模式;最后,以典型的社会系统——太湖流域复合系统为研究对象,采用"自上而下"与"自下而上"的研究思路,提出该系统情景近似可计算模式的研究方案,并分析政府不同偏好对该系统情景演化的影响,以期为社会系统研究提供新的理论元素和方法论指导.     

The Effects of Sharing Upstream Information on Product Rollover

The process of introducing new and phasing out old products is called product rollover. This paper considers a periodic‐review inventory system consisting of a manufacturer and a retailer, where the manufacturer introduces new and improved products over an infinite planning horizon using the solo‐roll strategy. We consider two scenarios: (1) the manufacturer does not share the upstream information about new‐product introduction with the retailer and (2) the manufacturer shares the information. For each scenario, we first derive the decentralized ordering policy and the system‐optimal ordering policy with given cost parameters. We then devise an optimal supply chain contract that coordinates the inventory system. We demonstrate that when the inventory system is coordinated, information sharing improves the performance of both supply chain entities. However, this may not be true if the inventory system is not coordinated. We also show that under the optimal contract, the manufacturer has no incentive to mislead the retailer about new‐product information in the information‐sharing model. When demand variability increases, information sharing adds more benefits to the coordinated supply chain. Our research provides insights about coordinating product, financial, and information flows in supply chains with product rollover.     

Time‐Series Models for Border Inspection Data

We propose a new modeling approach for inspection data that provides a more useful interpretation of the patterns of detections of invasive pests, using cargo inspection as a motivating example. Methods that are currently in use generally classify shipments according to their likelihood of carrying biosecurity risk material, given available historical and contextual data. Ideally, decisions regarding which cargo containers to inspect should be made in real time, and the models used should be able to focus efforts when the risk is higher. In this study, we propose a dynamic approach that treats the data as a time series in order to detect periods of high risk. A regulatory organization will respond differently to evidence of systematic problems than evidence of random problems, so testing for serial correlation is of major interest. We compare three models that account for various degrees of serial dependence within the data. First is the independence model where the prediction of the arrival of a risky shipment is made solely on the basis of contextual information. We also consider a Markov chain that allows dependence between successive observations, and a hidden Markov model that allows further dependence on past data. The predictive performance of the models is then evaluated using ROC and leakage curves. We illustrate this methodology on two sets of real inspection data.     

具有隐藏故障的多状态竞争失效系统检测策略研究

复杂工业系统的故障中有40%属于隐藏故障,若隐藏故障得不到及时消除,则可能导致巨大的经济损失。本文针对具有隐藏故障的多状态竞争失效系统,在考虑不完全检测的基础上,对其进行了维修建模。首先,基于制定的视情维修策略,分析了系统的更新情形;然后,基于所推导出的各种系统更新情形的发生概率,建立了以期望成本率为目标函数,以检测间隔时间为决策变量的维修模型。最后,以电容器组为例对所构建维修模型的适用性和有效性进行了验证,研究结果表明,检测质量对检测策略的制定有重要影响,因此研究具有隐藏故障的多状态竞争失效系统的检测策略时,有必要考虑检测误差。本文提出的维修建模方法不仅能在一定程度上丰富多状态竞争失效系统的维修策略理论与方法,还能为工程实际中复杂工业系统的维修工作提供理论基础与决策依据。     

Living with Nuclear Power: A Q-Method Study of Local Community Perceptions

The issue of new nuclear power is once again high up on the public policy agenda in many countries, and candidate sites for new civilian stations are likely to include those that have existing nuclear facilities. A common assumption is that existing nuclear communities will be more accepting of new build because of the direct economic and other benefits nuclear power already makes to a local area. Surprisingly, there is a dearth of contemporary data on perceptions of the risks, benefits, and values associated with nuclear power within such communities. This study uses Q-methodology to investigate the perspectives on living with nuclear risk among people ( n  = 84) drawn from communities near to two nuclear power stations in the United Kingdom. Both stations, at Bradwell-on-Sea and Oldbury-on-Severn, had been in operation for over 40 years. The Q-analysis identified four main perspectives, or points of view, accounting for 53% of total variance. These were interpreted as: Beneficial and Safe; Threat and Distrust; Reluctant Acceptance; and There's No Point Worrying. We conclude that the "landscape of beliefs" about nuclear power in such communities is both subtle and complex, avoiding simplistic bipolar dichotomies such as "for" or "against," and that there is a need for extensive and meaningful dialogue with such communities over any new build plans. The usefulness of Q-methodology for investigating the ways in which people live with risk is highlighted, as are the implications of the results for theories of risk and trust.     

When Does Poor Governance Presage Biosecurity Risk?

Border inspection, and the challenge of deciding which of the tens of millions of consignments that arrive should be inspected, is a perennial problem for regulatory authorities. The objective of these inspections is to minimize the risk of contraband entering the country. As an example, for regulatory authorities in charge of biosecurity material, consignments of goods are classified before arrival according to their economic tariff number. This classification, perhaps along with other information, is used as a screening step to determine whether further biosecurity intervention, such as inspection, is necessary. Other information associated with consignments includes details such as the country of origin, supplier, and importer, for example. The choice of which consignments to inspect has typically been informed by historical records of intercepted material. Fortunately for regulators, interception is a rare event; however, this sparsity undermines the utility of historical records for deciding which containers to inspect. In this article, we report on an analysis that uses more detailed information to inform inspection. Using quarantine biosecurity as a case study, we create statistical profiles using generalized linear mixed models and compare different model specifications with historical information alone, demonstrating the utility of a statistical modeling approach. We also demonstrate some graphical model summaries that provide managers with insight into pathway governance.     

DESIGNING INSPECTION STRATEGIES FOR UNCERTAIN ENVIRONMENTS

This paper considers the problems of designing inspection strategies for production systems terms in the presence of environmental uncertainty. The framework for determining information priorities to support inspection system planning is presented in the contaxt of a generic production system that encompasses the characteristics of many real-world serial production systems. The impact on the design decision of five key variables is considered: quality of producton processes, quality of inspection procedures, penalty cost for undetected defective units, relative cost of improving process vs. inspection, and shape of the cost functions for process and inspection enhancement. The framework for analysis involves varying factors over two or three orders of magnitude to determine optimal inspection strategies across a wide range of environments These results are used to compare design decisions made in the presence of environmental uncertainty using expected-opportunity-cost and minimization-of-maximum-opportunity-cost approaches. Design strategies are identified for situations ranging from complete lack of knowledge about the environment through increasing levels of information. Information-gathering priorities are established, and the impact on the design decision of this additional information is assayed.     

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。     

Service Package Switching in Hotel Revenue Management Systems

Revenue Management Systems (RMS) are commonly used in the hotel industry to maximize revenues in the short term. The forecasting‐allocation module is a key tactical component of a hotel RMS. Forecasting involves estimating demand for service packages across all stayover nights in a planning horizon. A service package is a unique combination of physical room, amenities, room price, and advance purchase restrictions. Allocation involves parsing the room inventory among these service packages to maximize revenues. Previous research and existing revenue management systems assume the demand for a service package to be independent of which service packages are available for sale. We develop a new forecasting‐allocation approach that explicitly accounts for this dependence. We compare the performance of the new approach against a baseline approach using a realistic hotel RMS simulation. The baseline approach reflects previous research and existing industry practice. The new approach produces an average revenue increase of at least 16% across scenarios that reflect existing industry conditions.     

Impact of Retailers with Knowledge of Supplier's Inventory on Supply Chain Performance

We model a supply chain consisting of a supplier and multiple retailers facing deterministic demand. We denote some retailers as strategic in the sense that given the supplier inventory information, they will implement the optimal stocking policy by incorporating such information. On the other hand, some retailers are denoted as naïve in the sense that they ignore supply information and resort to a simplistic ordering policy. Naïve retailers learn the optimal policy over time and adjust their orders accordingly. We study the dynamics of this game and investigate the impact of such strategic and naïve retailers on the cost, ordering pattern and stocking policies of all parties. We analyze the supply chain under two scenarios: the centralized supply chain where the objective is to minimize the total supply chain cost, and the decentralized supply chain where each self‐interested player minimizes its own cost in a Stackelberg game setting. We fully characterize the optimal policies under both centralized and decentralized scenarios and show that, surprisingly, the supply chain might be better off by virtue of naïve retailers. The result is driven by the fact that strategic and naïve players’ decisions shift the positioning of inventory in the supply chain with its final impact being determined by the relative costs of different retailer‐types. Our results also offer managerial insights into how access to supply information can improve supply chain performance.     

Optimal Randomized Scheduling by Replacement

In the replacement scheduling problem, a system consists of n processors drawn from a pool of p,all initially alive. At any time some processor can die. The scheduler is immediately informed of the fault butnot of its location. It must then choose another set of n processors. If this new set contains a dead processor, the system crashes and halts. The performance of a scheduling protocol is measured by the expected number of deaths the system tolerates before it crashes. We provide an optimal randomized scheduling protocol for this problem.The framework of this work combines an absolute performance measure for protocols and so-called adaptive online adversaries. This framework is rarely addressed because of the complexity of the interaction between protocols and adversaries. A major contribution of ourwork is to provide a theoretical foundation for the analysis of this interaction. In particular we make explicit how the protocol and the adversary affect the probability distribution of the analysis—a very general problem. We carefully analyze the exchange of sinformation between the two players, and reveal how they use their information optimally. The optimality of the protocol is established by using of a saddle point method for protocols and adversaries.     

Understanding Household Preferences for Hurricane Risk Mitigation Information: Evidence from Survey Responses

Risk information is critical to adopting mitigation measures, and seeking risk information is influenced by a variety of factors. An essential component of the recently adopted My Safe Florida Home (MSFH) program by the State of Florida is to provide homeowners with pertinent risk information to facilitate hurricane risk mitigation activities. We develop an analytical framework to understand household preferences for hurricane risk mitigation information through allowing an intensive home inspection. An empirical analysis is used to identify major drivers of household preferences to receive personalized information regarding recommended hurricane risk mitigation measures. A variety of empirical specifications show that households with home insurance, prior experience with damages, and with a higher sense of vulnerability to be affected by hurricanes are more likely to allow inspection to seek information. However, households with more members living in the home and households who live in manufactured/mobile homes are less likely to allow inspection. While findings imply MSFH program's ability to link incentives offered by private and public agencies in promoting mitigation, households that face a disproportionately higher level of risk can get priority to make the program more effective.     

The Detection of Nuclear Materials Losses*

The identification and location of materials losses in nuclear facilities is an important issue. Many complexities arise in monitoring such losses. These complexities include the dependency among materials balance observations and the influence of errors (outliers) on parameter estimates of various monitoring methods. The proposed Joint Estimation procedure is superior to standard methods (control chart and CUSUM) and to methods that build in correlation (ARMA control chart, ARMA CUSUM, and the Generalized M procedure) in the detection of nuclear materials losses. The Joint Estimation procedure is robust to the influence of outliers, is flexible in accommodating a range of dependencies among observations, and provides information on the type of loss. Further, the procedure is reliable in that it yields a probability of false alarms and a probability of detecting losses closer to specifications.     

Sourcing Through Auctions and Audits

Buyers often find that obtaining complete information about suppliers is costly. In such scenarios, there is a trade‐off between the costs of obtaining information and the benefits that accrue to the owners of such information. There are also various ways in which the missing information can be obtained or inferred. In this paper, we compare the efficiency of obtaining information via the classical mechanism design approach, which relies on the information available before the contracts are designed, with that of an “audit‐based” approach, which relies on the information obtained after the fact. In our model, a single buyer (the Stackelberg leader) wishes to procure a package of products or services from various competing suppliers that possess private cost information. We allow for arbitrary cost and revenue functions and can incorporate multiple cost and revenue drivers. We show how the buyer can optimize her profit and at the same time coordinate the channel by using a contract scheme involving auctions, audits, and profit sharing. We also examine the behavior of this mechanism when the supplier can exert effort to reduce cost but the cost of effort cannot be verified. We propose several mechanisms for different precontract informational scenarios and compare their performance.     

供应链中基于信息更新的订货时间及价格联合决策研究

文章考虑在信息可更新的情况下,由一个制造商和一个零售商组成的供应链中订货时间及价格的联合决策问题.在模型中,制造商为零售商提供多次订货时间选择及相应的订货价格,而零售商可以在销售季节开始前自由选择订货时间并享受相应的价格.文章以不同订货时间对信息更新程度的影响为着眼点,将订货时间作为内生决策变量,突破了已有文献中仅限于两次订货时间选择的局限,分别从集中决策和分散决策两个角度建立供应链节点企业的利润模型,并在分散决策情况下引入收益共享契约,寻找帕累托改进.最后通过数值试验证明了该模型的有效性.     

信息不对称对闭环供应链MTO和MTS模式的影响研究

在MTO(按订单生产)和MTS(按库存生产)两种模式下,比对了信息不对称和信息共享下产品定价、废旧品回收率和零售商利润的区别,研究结果显示:(1) 产品定价、废旧品回收率和零售商利润不受生产模式改变的影响;(2) 在某些条件下,信息共享下产品的批发价、零售价、和废旧品回收率均高于信息不对称时的相应值,进行信息共享会增加闭环供应链的总体利润,但零售商有可能通过信息共享丧失信息优势,从而使得其利润受损。因此为了促使零售商参与信息共享,信息共享参与方应投资建立安全的通信系统,以保证共享信息不被泄露。另外本文通过引入纳什讨价还价模型建立了一个公平的利润划拨机制,该机制使得最后的利润划分只取决于各参与方的议价能力,与各参与方对通信系统投资大小无关。     

Promoting Transparency of Long-Term Environmental Decisions: The Hanford Decision Mapping System Pilot Project

Nuclear waste cleanup is a challenging and complex problem that requires both scientific analysis and dialogue among a variety of stakeholders. This article describes an effort to develop an online information system that supports this analytic-deliberative dialogue by integrating cleanup information for the Hanford Site, and making it more "transparent." A framework for understanding and evaluating transparency guided system development. Working directly with stakeholders, we identified information needs and developed new ways to organize and present the information so that it would be more transparent to interested parties, with the ultimate aim of fostering greater participation in decision dialogues and processes. The complexity of the information needed for dialogue suggested that several types of communication devices ("information structures") were warranted. Five information structures were developed for the pilot Decision Mapping System (http://nalu.geog.washington.edu/dms). Decision maps hyperlinked decision information to maps of Hanford. Background Information provided context in a narrative format. Decision Paths organized decision process information on a timeline and provided direct hyperlinks to online documentation. The Geographic Library hyperlinked decision documents to maps. Finally, a Discussion Forum allowed users to make comments and view remarks from others. Early lessons from this work suggest that transparency is integral to long-term management, a participatory design process contributed greatly to its perceived success, and better data integration to support decision making is needed. This work has broad implications for risk communicators and risk managers because it speaks to the design of information systems to support "analytic-deliberative" decision processes (i.e., those that rely upon both risk science and public dialogue).     

Container Scheduling: Complexity and Algorithms

We consider the transport of containers through a fleet of ships. Each ship has a capacity constraint limiting the total number of containers it can carry and each ship visits a given set of ports following a predetermined route. Each container has a release date at its origination port, and a due date at its destination port. A container has a size 1 or size 2; size 1 represents a 1 TEU (20‐foot equivalent unit) and size 2 represents 2 TEUs. The delivery time of a container is defined as the time when the ship that carries the container arrives at its destination port. We consider the problem of minimizing the maximum tardiness over all containers. We consider three scenarios with regard to the routes of the ships, namely, the ships having (i) identical, (ii) nested, and (iii) arbitrary routes. For each scenario, we consider different settings for origination ports, release dates, sizes of containers, and number of ports; we determine the computational complexity of various cases. We also provide a simple heuristic for some cases, with its worst case analysis. Finally, we discuss the relationship of our problems with other scheduling problems that are known to be open.