顺序批量测试的通用框架

IF 0.9 4区管理学 Q4 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

Operations Research Letters Pub Date : 2025-07-29 DOI:10.1016/j.orl.2025.107348

Rayen Tan , Alex Xu , Viswanath Nagarajan

{"title":"顺序批量测试的通用框架","authors":"Rayen Tan , Alex Xu , Viswanath Nagarajan","doi":"10.1016/j.orl.2025.107348","DOIUrl":null,"url":null,"abstract":"<div><div>We provide a generic method that transforms a non-adaptive solution for classic sequential testing problems into a solution for the more general batched setting, while incurring only an additive <span><math><mfrac><mrow><mn>1</mn></mrow><mrow><msqrt><mrow><mn>2</mn></mrow></msqrt></mrow></mfrac></math></span> fraction loss in the approximation ratio. Combined with previously-known approximation algorithms in the classic setting, we obtain batched algorithms for AND, <em>k</em>-of-<em>n</em> and score-classification functions with approximation ratios 1.707, 2.618 and 6.371 respectively. Our algorithm is very efficient, running in <span><math><mi>O</mi><mo>(</mo><msup><mrow><mi>n</mi></mrow><mrow><mn>2</mn></mrow></msup><mo>)</mo></math></span> time for all the aforementioned functions.</div></div>","PeriodicalId":54682,"journal":{"name":"Operations Research Letters","volume":"63 ","pages":"Article 107348"},"PeriodicalIF":0.9000,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A general framework for sequential batch-testing\",\"authors\":\"Rayen Tan , Alex Xu , Viswanath Nagarajan\",\"doi\":\"10.1016/j.orl.2025.107348\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>We provide a generic method that transforms a non-adaptive solution for classic sequential testing problems into a solution for the more general batched setting, while incurring only an additive <span><math><mfrac><mrow><mn>1</mn></mrow><mrow><msqrt><mrow><mn>2</mn></mrow></msqrt></mrow></mfrac></math></span> fraction loss in the approximation ratio. Combined with previously-known approximation algorithms in the classic setting, we obtain batched algorithms for AND, <em>k</em>-of-<em>n</em> and score-classification functions with approximation ratios 1.707, 2.618 and 6.371 respectively. Our algorithm is very efficient, running in <span><math><mi>O</mi><mo>(</mo><msup><mrow><mi>n</mi></mrow><mrow><mn>2</mn></mrow></msup><mo>)</mo></math></span> time for all the aforementioned functions.</div></div>\",\"PeriodicalId\":54682,\"journal\":{\"name\":\"Operations Research Letters\",\"volume\":\"63 \",\"pages\":\"Article 107348\"},\"PeriodicalIF\":0.9000,\"publicationDate\":\"2025-07-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Operations Research Letters\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0167637725001099\",\"RegionNum\":4,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"OPERATIONS RESEARCH & MANAGEMENT SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Operations Research Letters","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0167637725001099","RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"OPERATIONS RESEARCH & MANAGEMENT SCIENCE","Score":null,"Total":0}

引用次数: 0

摘要

我们提供了一种通用方法，将经典序列测试问题的非自适应解决方案转换为更一般的批量设置的解决方案，同时在近似比率中只产生附加的12分数损失。结合经典设置下已知的近似算法，我们得到了近似比分别为1.707、2.618和6.371的AND、k (n)和分数分类函数的批处理算法。我们的算法非常高效，在O（n2）时间内运行上述所有函数。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

A general framework for sequential batch-testing

We provide a generic method that transforms a non-adaptive solution for classic sequential testing problems into a solution for the more general batched setting, while incurring only an additive

\frac{1}{\sqrt{2}}

fraction loss in the approximation ratio. Combined with previously-known approximation algorithms in the classic setting, we obtain batched algorithms for AND, k-of-n and score-classification functions with approximation ratios 1.707, 2.618 and 6.371 respectively. Our algorithm is very efficient, running in

O (n^{2})

time for all the aforementioned functions.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

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.