Efficient estimation of a risk measure requiring two-stage simulation optimization
Efficient estimation of a risk measure requiring two-stage simulation optimization
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DOI：
10.1016/j.ejor.2022.06.028
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发表时间：
2022-06
期刊：
影响因子：
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通讯作者：
Tianxiang Wang;Jie Xu;Jianqiang Hu;C.-H. Chen
中科院分区：
文献类型：
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作者：
Tianxiang Wang;Jie Xu;Jianqiang Hu;C.-H. Chen
本文关注的是系统风险度量的有效估计，其中估计需要解决两阶段模拟优化问题。第一阶段对指定第二阶段模拟优化问题的风险因素进行采样。第二阶段解决模拟优化问题，并输出系统在已实现的风险因素下的最佳性能，然后将所有第一阶段样本进行汇总，以生成风险度量的估计。这种估计方案的应用经常出现在金融、医疗保健、物流和制造等重要行业中。由于通常需要大量第一阶段样本，每个样本都需要解决计算成本高昂的仿真优化问题，因此两阶段仿真优化方法面临着计算效率的重大挑战。为了应对这一挑战，本文提出了一种顺序模拟预算分配程序，该程序根据每个场景下每个决策的符号变化修正概率的分数来确定模拟预算的分配。在金融投资组合风险估计和医疗保健系统弹性估计的背景下，使用基准测试函数和两个测试用例证明了所提出的程序的一致性，并证明了所提出的计算效率增益。
This paper is concerned with the efficient estimation of the risk measure of a system where the estimation requires solving a two-stage simulation optimization problem. The first stage samples risk factors that specify a second stage simulation optimization problem. The second stage solves a simulation optimization problem and outputs the best performance of the system under the realized risk factors, which are then aggregated across all first stage samples to produce an estimate of the risk measure. Applications of such an estimation scheme arise frequently in important industries such as financial, healthcare, logistics, and manufacturing. Because a large number of first stage samples are typically needed, each of which requires solving a computationally expensive simulation optimization problem, the two-stage simulation optimization approach faces a major computational efficiency challenge. In response to this challenge, this paper proposes a sequential simulation budget allocation procedure that determines the allocation of simulation budget based on a score known as revised probability of sign change for each decision under each scenario. The consistency of the proposed procedure is proved and the computational efficiency gain of the proposed is demonstrated using both benchmark test functions and two test cases in the context of financial portfolio risk estimation and healthcare system resilience estimation.