3,505 research outputs found

    A mathematical programming approach to railway network asset management

    Get PDF
    A main challenge in railway asset management is selecting the maintenance strategies to apply to each asset on the network in order to effectively manage the railway infrastructure given that some performance and safety targets have to be met under budget constraints. Due to economic, functional and operational dependencies between different assets and different sections of the network,# optimal solutions at network level not always include the best strategies available for each asset group. This paper presents a modelling approach to support decisions on how to effectively maintain a railway infrastructure system. For each railway asset, asset state models combining degradation and maintenance are used to assess the impact of any maintenance strategy on the future asset performance. The asset state models inform a network-level optimisation model aimed at selecting the best combination of maintenance strategies to manage each section of a given railway network in order to minimise the impact of the assets conditions on service, given budget constraints and performance targets. The optimisation problem is formulated as an integer-programming model. By varying the model parameters, scenario analysis can be performed so that the infrastructure manager is provided with a range of solutions for different combination of budget available and performance targets

    On the connections among activity-based costing, mathematical programming models for analyzing strategic decisions, and the resource based view of the firm

    Get PDF
    Title from cover. "April, 1998"--Cover. -- "December, 1997"--Pref.Includes bibliographical references (p. 31-33).Jeremy F. Shapiro

    Bank Lending, Housing and Spreads

    Get PDF
    The framework presented in this paper takes its cue from recent financial events and attempts to develop a tractable framework for policy analysis of macro-linkages, in particular a first attempt at the integration of an independent profit-maximising banking sector that lends to and borrows from agents in the economy, and through which changes in the monetary policy rate by the central bank are transmitted. The inter-linkages between housing and the role of the banking sector in the transmission of monetary policy is emphasized. Two competing effects are highlighted: (i) a financial accelerator channel, due to the presence of collateralized borrowers, and (ii) a banking attenuator effect, which crucially arises from the spread in interest rates caused by the introduction of monopolistically competitive financial intermediaries. We show how the classical amplification mechanism explored in models of private borrowing between collaterally-constrained 'impatient' households and unconstrained 'patient' households, such as those put forward by Kiyotaki and Moore (1997) and Iacoviello (2005), is counteracted by the banking attenuator effect, given an endogenous steady state spread between loan and savings rates. Attenuation occurs therefore even under the assumption of flexible interest rates. This effect is further magnified when sluggishness in the interest rate-setting mechanism is introduced.bank lending; housing; liquidity; credit; staggered interest rate-setting; collateral constraints

    Extending Cyber-Physical Systems to Support Stakeholder Decisions Under Resource and User Constraints: Applications to Intelligent Infrastructure and Social Urban Systems

    Full text link
    In recent years, rapid urbanization has imposed greater load demands on physical infrastructure while placing stressors (e.g., pollution, congestion, social inequity) on social systems. Despite these challenges, opportunities are emerging from the unprecedented proliferation of information technologies enabling ubiquitous sensing, cloud computing, and full-scale automation. Together, these advancements enable “intelligent” systems that promise to enhance the operation of the built environment. Even with these advancements, the ability of professionals to “sense for decisions” —data-driven decision processes based on sensed data that have quantifiable returns on investment—remains unrealized for an entire class of problems. In response, this dissertation builds a rigorous foundation enabling stakeholders to use sensor data to inform decisions in two applications: infrastructure asset management and community-engaged decision making. This dissertation aligns sensing strategies with decisions governing infrastructure management by extending the role of reliability methods to quantify system performance. First, the reliability index is used as a scalar measure of the safety (i.e., failure probability) that is extracted from monitoring data to assess structural condition relative to a failure limit state. As an example, long-term data collected from a wireless sensing network (WSN) installed on the Harahan Bridge (Memphis, TN) is used in a reliability framework to track the fatigue life of critical eyebar assemblies. The proposed reliability-based SHM framework is then generalized to formally and more broadly link SHM data with condition ratings (CRs) because inspector-assigned CRs remain the primary starting point for asset management decisions made in practice today. While reliability methods historically quantify safety with respect to a single failure limit state, this work demonstrates that there exist measurable reliability index values associated with “lower” limit states below failure that more richly characterize structural performance and rationally map to CR scales. Consequently, monitoring data can be used to assign CRs based on quantitative information encompassing the measurable damage domain, as opposed to relying on visual inspection. This work reflects the first-ever SHM framework to explicitly map monitoring data to actionable decisions and is validated using a WSN on the Telegraph Road Bridge (TRB) (Monroe, MI). A primary challenge faced by solar-powered WSNs is their stringent energy constraints. For decision-making processes relying on statistical estimation of performance, the utility of data should be considered to optimize the data collection process given these constraints. This dissertation proposes a novel stochastic data collection and transmission policy for WSNs that minimizes the variance of a measured process’ estimated parameters subject to constraints imposed by energy and data buffer sizes, stochastic models of energy and event arrivals, the value of measured data, and temporal death. Numerical results based on one-year of data collected from the TRB illustrate the gains achieved by implementing the optimal policy to obtain response data used to estimate the reliability index. Finally, this dissertation extends the work performed in WSN and sense-for-decision frameworks by exploring their role in community-based decision making. This work poses societal engagement as a necessary entry point to urban sensing efforts because members of under-resourced communities are vulnerable to lack of access to data and information. A novel, low-power WSN architecture is presented that functions as a user-friendly sensing solution that communities can rapidly deploy. Applying this platform, transformative work to “democratize” data is proposed in which members of vulnerable communities collect data and generate insights that inform their decision-making strategies.PHDCivil EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/162898/1/kaflanig_1.pd

    Sovereign risk, interbank freezes, and aggregate fluctuations

    Get PDF
    This paper studies the bank-sovereign link in a dynamic stochastic general equilibrium set-up with strategic default on public debt. Heterogeneous banks give rise to an interbank market where government bonds are used as collateral. A default penalty arises from a breakdown of interbank intermediation that induces a credit crunch. Government borrowing under limited commitment is costly ex ante as bank funding conditions tighten when the quality of collateral drops. This lowers the penalty from an interbank freeze and feeds back into default risk. The arising amplification mechanism propagates aggregate shocks to the macroeconomy. The model is calibrated using Spanish data and is capable of reproducing key business cycle statistics alongside stylized facts during the European sovereign debt crisis

    Expectations, employment and prices: a suggested interpretation of the new 'farmerian' economics

    Get PDF
    This paper aims at providing a critical assessment of the new ‘Farmerian’ economics, i.e. the recent Farmer’s attempt to provide a new micro-foundation of the General Theory grounded on modern search and business cycle theories. Specifically, I develop a theoretical model that summarizes the main arguments of the suggested approach by showing that a special importance has to be attached to the search mechanism, the choice of units and ‘animal spirits’ modelling. Thereafter, referring to self-made real-business-cycle experiments, I discuss the main empirical implications of the resulting framework. Finally, I consider its policy implications by stressing the problematic nature of demand management interventions and the advisability of extending the role of the central bank in preventing financial bubbles and crashes.Old Keynesian Economics; search; demand constrained equilibrium; Shimer puzzle; economic policy.

    Risk-Based Optimal Scheduling for the Predictive Maintenance of Railway Infrastructure

    Get PDF
    In this thesis a risk-based decision support system to schedule the predictive maintenance activities, is proposed. The model deals with the maintenance planning of a railway infrastructure in which the due-dates are defined via failure risk analysis.The novelty of the approach consists of the risk concept introduction in railway maintenance scheduling, according to ISO 55000 guidelines, thus implying that the maintenance priorities are based on asset criticality, determined taking into account the relevant failure probability, related to asset degradation conditions, and the consequent damages

    The transformation of the Afar commons in Ethiopia: State coercion, diversification and property rights change among pastoralists

    Get PDF
    "The major economic activity for pastoralists is animal husbandry. The harsh environment in which herders raise their livestock requires constant mobility to regulate resource utilisation via a common property regime. In contrast to the mobile way of life characterizing pastoralism, agriculture as a sedentary activity is only marginally present in the lowlands of the Afar regional state in Ethiopia. Nevertheless, this study reveals a situation where the traditional land-use arrangements in Afar are being transformed due to the introduction of farming. In the past, the Imperial and the Socialist governments introduced large-scale agriculture in a coercive manner, thereby instigating massive resistance from the pastoralists. Currently, the recurrence of drought in the study areas has facilitated the subdivision of the communal land on a voluntary basis for the purpose of farming. Qualitative and quantitative analysis highlight the drivers, both coercive and non-coercive, of the transformation of traditional property rights of Afar pastoralists." authors' abstractPastoralism, livestock, Property rights, Rangeland management, Communal land, Environmental management,
    • 

    corecore