Impact of Asset Utilization on Replacement Decisions

哈特曼9713690 这笔赠款为开发一个优化工具提供资金，以确定在随机作业环境下对一组资产的更换决定。 传统的模式，提供更换决策离散（每年）的时间间隔，是基于预期的运营，维护和救助成本，这是取决于资产利用率水平确定的运营（日常）的决定。然而，由于与业务有关的不确定性，如需求或预算水平波动，这些预期的利用水平在实践中可能无法实现，从而使更换时间表无效。 该研究将把战略（更换）和业务（利用）决策联系起来，使更换时间表成为资产利用的函数。 这个问题将在运输行业的背景下进行研究，赞助商包括一家铁路公司和一家卡车租赁公司。 研究了一种双端排队模型，用以近似描述运输系统的运行情况，并确定运输系统的利用水平。 该模型被构建成一个非线性优化模型， 成本采购和销售决策。 大规模非线性规划的研究求解过程是基于增广拉格朗日技术。 这项研究在工业和军事领域有许多潜在的应用，因为这些组织通常依赖于在不确定环境中利用率不同的资产组或资产队。 分析将合并两个传统上独立的决策，静态替换问题和动态运营问题， 资本预算的决定是基于对实际业务的衡量。 由于购置决策取决于资产利用率，该模型将改进资产置换决策 传统上依赖于静态数据的过程。 这项研究也将有助于改进大规模非线性优化模型的求解技术，并为双端队列提供更多的研究，尽管它们有许多应用，但在 research.

Hartman 9713690 This grant provides funding for the development of an optimization tool to determine replacement decisions for a group of assets subject to a random operational environment. Traditional models, which provide replacement decisions over discrete (annual) intervals, are based on expected operating, maintenance and salvage costs which are dependent on asset utilization levels determined by operational (daily) decisions. However, due to uncertainty associated with operations, such as fluctuating demand or budget levels, these expected utilization levels may not be realized in practice, thus invalidating the replacement schedule. The research will link strategic (replacement) and operational (utilization) decisions such that replacement schedules are functions of asset utilization. This problem will be examined in the context of the transportation industry, with sponsors including a railroad and a truck leasing firm. A double-ended queueing model is researched to approximate the operations of the transportation system and determine utilization levels. This model is built into a non-linear optimization model which determines minimum cost purchase and sale decisions. The research solution procedure for the large scale non-linear program is based on augmented Lagrangian techniques. There are numerous potential applications of this research in industry and the military as these organizations generally rely on groups or fleets of assets which are subject to varying levels of utilization in an uncertain environment. The analysis will merge two traditionally separate decisions, the static replacement problem and the dynamic operational problem, such that strategic capital budgeting decisions are based on a measurement of actual operations. As acquisition decisions are dependent on asset utilization, the model will improve the asset replacement decision process which traditionally relies on static data. This research will also contribute to improved solution techniques for large scale non-linear optimization models and provide more investigation into double-ended queues which despite their numerous applications are not prominent in research.