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Optimal resource allocation among transit agencies for fleet management

机译:在运输机构之间优化资源分配以进行车队管理

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摘要

Most transit agencies require government support for the replacement of their aging fleet. A procedure for equitable resource allocation among competing transit agencies for the purpose of transit fleet management is presented in this study. The proposed procedure is a 3-dimensional model that includes the choice of a fleet improvement program, agencies that may receive them, and the timing of investments. Earlier efforts to solve this problem involved the application of 1- or 2-dimensional models for each year of the planning period. These may have resulted in suboptimal solution as the models are blind to the impact of the fleet management program of the subsequent years. Therefore, a new model to address a long-term planning horizon is proposed. The model is formulated as a non-linear optimization problem of maximizing the total weighted average remaining life of the fleet subjected to improvement program and budgetary constraints. Two variants of the problem, one with an annual budget constraint and the other with a single budget constraint for the entire planning period, are formulated. Two independent approaches, namely, branch and bound algorithm and genetic algorithm are used to obtain the solution. An example problem is solved and results are discussed in details. Finally, the model is applied to a large scale real-world problem and a detailed analysis of the results is presented.
机译:大多数运输机构都需要政府的支持来更换老化的车队。本研究提出了一种在竞争性运输机构之间公平分配资源的程序,以管理运输车队。拟议的程序是一个3维模型,其中包括机队改进计划的选择,可能接受该计划的机构以及投资时机。解决此问题的早期工作涉及在计划周期的每一年中应用一维或二维模型。由于这些模型对随后几年的车队管理计划的影响视而不见,因此可能导致解决方案不理想。因此,提出了一种解决长期规划问题的新模型。该模型被公式化为一个非线性优化问题,该问题使受改进计划和预算约束的车队的总加权平均剩余寿命最大化。提出了该问题的两种变体,一种在整个计划期间都具有年度预算约束,而另一种具有单个预算约束。求解采用分支定界算法和遗传算法两种独立的方法。解决了一个示例问题,并详细讨论了结果。最后,将该模型应用于大规模的现实世界问题,并对结果进行详细分析。

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