Finding a good normal population

IF 0.8 4区管理学 Q4 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

Operations Research Letters Pub Date : 2025-03-31 DOI:10.1016/j.orl.2025.107281

Sheldon M. Ross, Tianchi Zhao

引用次数: 0

Abstract

We study the problem of finding a normal population whose mean is at least as large as some specified value m. Assuming a sampling cost, the objective is to minimize the expected total discounted cost until there is a population whose mean is at least m with probability at least α. We propose several heuristic policies as well as a linear programming approach.

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找到一个良好的正常人口

我们研究了寻找均值至少等于某个规定值m的正态总体的问题。假设一个抽样成本，目标是最小化期望总贴现成本，直到存在均值至少为m且概率至少为α的总体。我们提出了几种启发式策略以及线性规划方法。

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

Operations Research Letters 管理科学-运筹学与管理科学

CiteScore

2.10

自引率

9.10%

发文量

111

审稿时长

83 days

期刊介绍： Operations Research Letters is committed to the rapid review and fast publication of short articles on all aspects of operations research and analytics. Apart from a limitation to eight journal pages, quality, originality, relevance and clarity are the only criteria for selecting the papers to be published. ORL covers the broad field of optimization, stochastic models and game theory. Specific areas of interest include networks, routing, location, queueing, scheduling, inventory, reliability, and financial engineering. We wish to explore interfaces with other fields such as life sciences and health care, artificial intelligence and machine learning, energy distribution, and computational social sciences and humanities. Our traditional strength is in methodology, including theory, modelling, algorithms and computational studies. We also welcome novel applications and concise literature reviews.