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Interval-Parameter Conditional Value-at-Risk Two-Stage Stochastic Programming Model for Management of End-of-Life Vehicles

机译:报废车辆管理的区间参数条件风险两阶段随机规划模型

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The management of end-of-life vehicles conserves natural resources, provides economic benefits, and reduces water, air, and soil pollution. Sound management of end-of-life vehicles is vitally important worldwide thus requiring sophisticated decision-making tools for optimizing its efficiency and reducing system risk. This paper proposes an interval-parameter conditional value-at-risk two-stage stochastic programming model for management of end-of-life vehicles. A case study is conducted in order to demonstrate the usefulness of the developed model. The model is able to provide the trade-offs between the expected profit and system risk. It can effectively control risk at extremely disadvantageous availability levels of end-of-life vehicles. The formulated model can produce optimal solutions under predetermined decision-making risk preferences and confidence levels. It can simultaneously determine the optimal long-term allocation targets of end-of-life vehicles and reusable parts as well as capital investment, production planning, and logistics management decisions within a multi-period planning horizon. The proposed model can efficiently handle uncertainties expressed as interval values and probability distributions. It is able to provide valuable insights into the effects of uncertainties. Compared to the available models, the resulting solutions are far more robust.
机译:报废车辆的管理可以节省自然资源,提供经济利益并减少水,空气和土壤污染。报废车辆的良好管理在全球范围内至关重要,因此需要完善的决策工具来优化其效率并降低系统风险。提出了一种报废车辆管理的区间参数条件风险两阶段随机规划模型。为了证明所开发模型的有用性,进行了案例研究。该模型能够在预期利润和系统风险之间进行权衡。它可以在报废车辆的极为不利的可用性水平下有效地控制风险。制定的模型可以在预定的决策风险偏好和置信度下产生最佳解决方案。它可以在多个时期的计划范围内同时确定报废车辆和可重复使用零件的最佳长期分配目标,以及资本投资,生产计划和物流管理决策。所提出的模型可以有效地处理表示为区间值和概率分布的不确定性。它能够为不确定性的影响提供有价值的见解。与可用模型相比,最终的解决方案更加健壮。

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