An Approximation to the Invariant Measure of the Limiting Diffusion of G/Ph/n + GI Queues in the Halfin–Whitt Regime and Related Asymptotics

IF 1.4 3区 数学 Q2 MATHEMATICS, APPLIED
Xinghu Jin, Guodong Pang, Lihu Xu, Xin Xu
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引用次数: 0

Abstract

In this paper, we develop a stochastic algorithm based on the Euler–Maruyama scheme to approximate the invariant measure of the limiting multidimensional diffusion of [Formula: see text] queues in the Halfin–Whitt regime. Specifically, we prove a nonasymptotic error bound between the invariant measures of the approximate model from the algorithm and the limiting diffusion. To establish the error bound, we employ the recently developed Stein’s method for multidimensional diffusions, in which the regularity of Stein’s equation obtained by the partial differential equation (PDE) theory plays a crucial role. We further prove the central limit theorem (CLT) and the moderate deviation principle (MDP) for the occupation measures of the limiting diffusion of [Formula: see text] queues and its Euler–Maruyama scheme. In particular, the variances in the CLT and MDP associated with the limiting diffusion are determined by Stein’s equation and Malliavin calculus, in which properties of a mollified diffusion and an associated weighted occupation time play a crucial role.Funding: X. Jin is supported in part by the Fundamental Research Funds for the Central Universities [Grants JZ2022HGQA0148 and JZ2023HGTA0170]. G. Pang is supported in part by the U.S. National Science Foundation [Grants DMS-1715875 and DMS-2216765]. L. Xu is supported in part by the National Nature Science Foundation of China [Grant 12071499], Macao Special Administrative Region [Grant FDCT 0090/2019/A2], and the University of Macau [Grant MYRG2018-00133-FST]. This work was supported by U.S. National Science Foundation [Grant DMS-2108683].
Halfin-Whitt 状态下 G/Ph/n + GI 队列极限扩散的不变量近似值及相关渐近线
在本文中,我们开发了一种基于欧拉-Maruyama 方案的随机算法,用于近似 Halfin-Whitt 体系中[公式:见正文]队列的极限多维扩散的不变度量。具体地说,我们证明了算法近似模型的不变度量与极限扩散之间的非渐近误差约束。为了建立误差约束,我们采用了最近开发的斯坦因多维扩散方法,其中由偏微分方程(PDE)理论得到的斯坦因方程的正则性起着至关重要的作用。我们进一步证明了[公式:见正文]队列及其欧拉-马鲁山方案的极限扩散的占用度量的中心极限定理(CLT)和适度偏差原理(MDP)。特别是,与极限扩散相关的 CLT 和 MDP 中的方差是由斯坦因方程和马利亚文微积分决定的,其中软化扩散和相关加权占用时间的特性起着至关重要的作用:X. Jin 的部分研究经费来自中央高校基本科研业务费[JZ2022HGQA0148 和 JZ2023HGTA0170]。G. Pang 得到美国国家科学基金会[Grants DMS-1715875 and DMS-2216765] 的部分资助。L. Xu 的部分研究工作得到国家自然科学基金委员会 [Grant 12071499]、澳门特别行政区 [Grant FDCT 0090/2019/A2] 和澳门大学 [Grant MYRG2018-00133-FST] 的支持。这项工作得到了美国国家科学基金会[DMS-2108683号资助]的支持。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Mathematics of Operations Research
Mathematics of Operations Research 管理科学-应用数学
CiteScore
3.40
自引率
5.90%
发文量
178
审稿时长
15.0 months
期刊介绍: Mathematics of Operations Research is an international journal of the Institute for Operations Research and the Management Sciences (INFORMS). The journal invites articles concerned with the mathematical and computational foundations in the areas of continuous, discrete, and stochastic optimization; mathematical programming; dynamic programming; stochastic processes; stochastic models; simulation methodology; control and adaptation; networks; game theory; and decision theory. Also sought are contributions to learning theory and machine learning that have special relevance to decision making, operations research, and management science. The emphasis is on originality, quality, and importance; correctness alone is not sufficient. Significant developments in operations research and management science not having substantial mathematical interest should be directed to other journals such as Management Science or Operations Research.
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