Impact of Asset Utilization on Replacement Decisions

哈特曼9713690这笔赠款为开发一种优化工具提供资金，以确定受随机运营环境影响的一组资产的替换决策。传统模型在离散的(年度)间隔内提供更换决策，其基础是预期的运营、维护和打捞成本，这些成本取决于由运营(每日)决策确定的资产利用率水平。然而，由于与业务相关的不确定性，如需求或预算水平的波动，这些预期的利用率水平在实践中可能无法实现，从而使更换时间表失效。这项研究将把战略(替换)和业务(使用)决策联系起来，使替换时间表成为资产使用的功能。这个问题将在运输业的背景下进行审查，赞助商包括一家铁路和一家卡车租赁公司。研究了一个双端排队模型，以近似描述运输系统的运行情况，并确定系统的利用率水平。该模型被构建为一个确定最小成本购销决策的非线性优化模型。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的。这项研究在工业和军事中有许多潜在的应用，因为这些组织通常依赖于在不确定环境中受到不同程度利用的资产集团或舰队。分析将合并两个传统上分开的决策，即静态替代问题和动态业务问题，从而使战略资本预算决策基于对实际业务的衡量。由于收购决策依赖于资产利用率，该模型将改进传统上依赖静态数据的资产置换决策流程。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，并为双端排队提供更多的研究，尽管双端排队有着众多的应用，但研究并不突出。

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.