On the optimal design of the randomized unbiased Monte Carlo estimators

被引：0

作者：

Cui, Zhenyu ^{[1
]}

Lee, Chihoon ^{[1
]}

Zhu, Lingjiong ^{[2
]}

Zhu, Yunfan ^{[1
]}

机构：

[1] Stevens Inst Technol, Sch Business, Hoboken, NJ 07030 USA

[2] Florida State Univ, Dept Math, Tallahassee, FL 32304 USA

来源：

OPERATIONS RESEARCH LETTERS | 2021年 / 49卷 / 04期

关键词：

Simulation; Unbiased estimation; Simulation optimization; EFFICIENT SIMULATION; RESOURCE-ALLOCATION;

D O I：

10.1016/j.orl.2021.05.004

中图分类号：

C93 [管理学]; O22 [运筹学];

学科分类号：

070105 ; 12 ; 1201 ; 1202 ; 120202 ;

摘要：

We consider a class of unbiased Monte Carlo estimators and develop an efficient algorithm to produce the distribution of the optimal random truncation level. We establish the convergence and optimality results of the associated algorithm and also derive its exact complexity. We find this algorithm has a much lower complexity as compared to the existing one in the literature. The proposed algorithm is also applicable to optimization problems arising in supply chain management, such as economic reorder interval problem. (C) 2021 Elsevier B.V. All rights reserved.

引用

页码：477 / 484

页数：8

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