• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文学位 >Real Options Models for Better Investment Decisions in Road Infrastructure under Demand Uncertainty
【24h】

Real Options Models for Better Investment Decisions in Road Infrastructure under Demand Uncertainty

机译：需求不确定性下用于改善道路基础设施投资决策的实物期权模型

获取原文
获取原文并翻译 | 示例
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

An efficient transportation system requires adequate and well-maintained infrastructure to relieve congestion, reduce accidents, and promote economic competitiveness. However, there is a growing gap between public financial commitments and the cost of maintaining, let alone expanding the U.S. road transportation infrastructure. Moreover, the tools used to evaluate transportation infrastructure investments are typically deterministic and rely on present value calculations, even though it is well-known that this approach is likely to result in sub-optimal decisions in the presence of uncertainty, which is pervasive in transportation infrastructure decisions. In this context, the purpose of this dissertation is to propose a framework based on real options and advanced numerical methods to make better road infrastructure decisions in the presence of demand uncertainty.;I first develop a real options framework to find the optimal investment timing, endogenous toll rate, and road capacity of a private inter-city highway under demand uncertainty. Traffic congestion is represented by a BPR function, competition with an existing road is captured by user equilibrium, and travel demand between the two cities follows a geometric Brownian motion with a reflecting upper barrier. I derive semi-analytical solutions for the investment threshold, the dynamic toll rates and the optimum capacity. The result shows the importance of modeling congestion and an upper demand barrier -- features that are missing from previous studies.;I then extend this real options framework to study two additional ways of funding an inter-city highway project: with public funds or via a Public-Private Partnership (PPP). Using Monte Carlo simulation, I investigate the value of a non-compete clause for both a local government and for private firms involved in the PPP.;Since road infrastructure investments are rarely made in isolation, I also extend my real options framework to the multi-period Continuous Network Design Problem (CNDP), to analyze the investment timing and capacity of multiple links under demand uncertainty. No algorithm is currently available to solve the multi-period CNDP under uncertainty in a reasonable time. I propose and test a new algorithm called "Approximate Least Square Monte Carlo simulation" that dramatically reduces the computing time to solve the CNDP while generating accurate solutions.
机译：高效的运输系统需要充足且维护良好的基础设施，以缓解交通拥堵，减少事故并提高经济竞争力。但是，公共财政承诺与维护成本之间的差距越来越大，更不用说扩大美国的道路运输基础设施了。此外，用于评估运输基础设施投资的工具通常是确定性的，并依赖于现值计算，即使众所周知，在存在不确定性的情况下，这种方法很可能导致次优决策，这在运输中普遍存在基础设施决策。在这种情况下，本文的目的是提出一个基于实物期权和高级数值方法的框架，以在存在需求不确定性的情况下做出更好的道路基础设施决策。我首先开发一个实物期权框架以找到最佳投资时机，需求不确定性下的内生收费率和城际专用公路的通行能力。交通拥堵由BPR函数表示，与现有道路的竞争由用户平衡捕获，两个城市之间的出行需求遵循具有反射性上限的几何布朗运动。我得出了投资门槛，动态通行费率和最佳通行能力的半解析解决方案。结果显示了对拥堵和高需求障碍进行建模的重要性-先前研究中缺少的功能;然后我扩展了该实物期权框架，以研究为城际公路项目提供资金的两种其他方式：通过公共资金或公私伙伴关系（PPP）。通过蒙特卡洛模拟，我研究了不竞争条款对地方政府和参与PPP的私营公司的价值。由于道路基础设施投资很少是孤立进行的，因此我还将实物期权框架扩展到了多边投资周期连续网络设计问题（CNDP），以分析需求不确定情况下多链路的投资时机和容量。目前尚无算法可在合理时间内解决不确定性下的多期CNDP。我提出并测试了一种称为“近似最小二乘蒙特卡洛模拟”的新算法，该算法可显着减少计算时间来解决CNDP，同时生成精确的解决方案。

著录项

  • 作者

    Wang, Ke.;

  • 作者单位

    University of California, Irvine.;

  • 授予单位 University of California, Irvine.;
  • 学科 Civil engineering.
  • 学位 Ph.D.
  • 年度 2017
  • 页码 149 p.
  • 总页数 149
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号