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Enhanced least squares Monte Carlo method for real-time decision optimizations for evolving natural hazards

机译：增强的最小二乘蒙特卡洛方法，用于不断发展的自然灾害的实时决策优化

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摘要

The present paper aims at enhancing a solution approach proposed by Anders & Nishijima (2011) to real-time decision problems in civil engineering. The approach takes basis in the Least Squares Monte Carlo method (LSM) originally proposed by Longstaff & Schwartz (2001) for computing American option prices. In Anders & Nishijima (2011) the LSM is adapted for a real-time operational decision problem; however it is found that further improvement is required in regard to the computational efficiency, in order to facilitate it for practice. This is the focus in the present paper. The idea behind the improvement of the computational efficiency is to "best utilize" the least squares method; i.e. least squares method is applied for estimating the expected utility for terminal decisions, conditional on realizations of underlying random phenomena at respective times in a parametric way. The implementation and efficiency of the enhancement is shown with an example on evacuation in an avalanche risk situation.
机译：本文旨在增强由Anders＆Nishijima（2011）提出的解决方案方法，以解决土木工程中的实时决策问题。该方法基于Longstaff＆Schwartz（2001）最初提出的最小二乘蒙特卡洛方法（LSM），用于计算美国期权价格。在Anders＆Nishijima（2011）中，LSM适用于实时操作决策问题。然而，发现为了提高计算效率，需要对计算效率进行进一步的改进。这是本文的重点。改进计算效率的思想是“最佳利用”最小二乘法。即，最小二乘法被用于估计终端决策的预期效用，条件是在相应时间以参数方式实现潜在的随机现象。通过雪崩风险情况下的疏散示例显示了增强功能的实施和效率。

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  • 会议地点 Yerevan(AM)
  • 作者

    A. Anders; K. Nishijima;

  • 作者单位

    Department of Civil Engineering, Technical University of Denmark, Denmark;

    Department of Civil Engineering, Technical University of Denmark, Denmark;

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  • 正文语种 eng
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