{"title":"Two measures of efficiency for the secretary problem with multiple items at each rank","authors":"Ross G. Pinsky","doi":"10.1016/j.aam.2024.102751","DOIUrl":null,"url":null,"abstract":"<div><p>For <span><math><mn>2</mn><mo>≤</mo><mi>k</mi><mo>∈</mo><mi>N</mi></math></span>, consider the following adaptation of the classical secretary problem. There are <em>k</em> items at each of <em>n</em> linearly ordered ranks. The <em>kn</em> items are revealed, one item at a time, in a uniformly random order, to an observer whose objective is to select an item of highest rank. At each stage the observer only knows the relative ranks of the items that have arrived thus far, and must either select the current item, in which case the process terminates, or reject it and continue to the next item. For <span><math><mi>M</mi><mo>∈</mo><mo>{</mo><mn>0</mn><mo>,</mo><mn>1</mn><mo>,</mo><mo>⋯</mo><mo>,</mo><mi>k</mi><mi>n</mi><mo>−</mo><mn>1</mn><mo>}</mo></math></span>, let <span><math><mi>S</mi><mo>(</mo><mi>n</mi><mo>,</mo><mi>k</mi><mo>;</mo><mi>M</mi><mo>)</mo></math></span> denote the strategy whereby one allows the first <em>M</em> items to pass, and then selects the first later arriving item whose rank is either equal to or greater than the highest rank of the first <em>M</em> items (if such an item exists). Let <span><math><msub><mrow><mi>W</mi></mrow><mrow><mi>S</mi><mo>(</mo><mi>n</mi><mo>,</mo><mi>k</mi><mo>;</mo><mi>M</mi><mo>)</mo></mrow></msub></math></span> denote the event that one selects an item of highest rank using strategy <span><math><mi>S</mi><mo>(</mo><mi>n</mi><mo>,</mo><mi>k</mi><mo>;</mo><mi>M</mi><mo>)</mo></math></span> and let <span><math><msub><mrow><mi>P</mi></mrow><mrow><mi>n</mi><mo>,</mo><mi>k</mi></mrow></msub><mo>(</mo><msub><mrow><mi>W</mi></mrow><mrow><mi>S</mi><mo>(</mo><mi>n</mi><mo>,</mo><mi>k</mi><mo>;</mo><mi>M</mi><mo>)</mo></mrow></msub><mo>)</mo></math></span> denote the corresponding probability. We obtain a formula for <span><math><msub><mrow><mi>P</mi></mrow><mrow><mi>n</mi><mo>,</mo><mi>k</mi></mrow></msub><mo>(</mo><msub><mrow><mi>W</mi></mrow><mrow><mi>S</mi><mo>(</mo><mi>n</mi><mo>,</mo><mi>k</mi><mo>;</mo><mi>M</mi><mo>)</mo></mrow></msub><mo>)</mo></math></span>, and for <span><math><msub><mrow><mi>lim</mi></mrow><mrow><mi>n</mi><mo>→</mo><mo>∞</mo></mrow></msub><mo></mo><msub><mrow><mi>P</mi></mrow><mrow><mi>n</mi><mo>,</mo><mi>k</mi></mrow></msub><mo>(</mo><msub><mrow><mi>W</mi></mrow><mrow><mi>S</mi><mo>(</mo><mi>n</mi><mo>,</mo><mi>k</mi><mo>;</mo><msub><mrow><mi>M</mi></mrow><mrow><mi>n</mi></mrow></msub><mo>)</mo></mrow></msub><mo>)</mo></math></span>, when <span><math><msub><mrow><mi>M</mi></mrow><mrow><mi>n</mi></mrow></msub><mo>∼</mo><mi>c</mi><mi>k</mi><mi>n</mi></math></span>, with <span><math><mi>c</mi><mo>∈</mo><mo>(</mo><mn>0</mn><mo>,</mo><mn>1</mn><mo>)</mo></math></span>. In the classical secretary problem (<span><math><mi>k</mi><mo>=</mo><mn>1</mn></math></span>), the asymptotic probability of success using an optimal strategy is <span><math><mfrac><mrow><mn>1</mn></mrow><mrow><mi>e</mi></mrow></mfrac><mo>≈</mo><mn>0.368</mn></math></span>. For <span><math><mi>k</mi><mo>=</mo><mn>2</mn></math></span>, the asymptotic probability of success using an optimal strategy from the above class is about 0.701. For <span><math><mi>k</mi><mo>=</mo><mn>7</mn></math></span>, that probability already exceeds 0.99. In the problem with multiple items at each rank, there is an additional measure of efficiency of a strategy besides the probability of selecting an item of highest rank; namely how quickly one selects an item of highest rank. We give a rather complete picture of this efficiency.</p></div>","PeriodicalId":50877,"journal":{"name":"Advances in Applied Mathematics","volume":null,"pages":null},"PeriodicalIF":1.0000,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Applied Mathematics","FirstCategoryId":"100","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0196885824000836","RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
引用次数: 0
Abstract
For , consider the following adaptation of the classical secretary problem. There are k items at each of n linearly ordered ranks. The kn items are revealed, one item at a time, in a uniformly random order, to an observer whose objective is to select an item of highest rank. At each stage the observer only knows the relative ranks of the items that have arrived thus far, and must either select the current item, in which case the process terminates, or reject it and continue to the next item. For , let denote the strategy whereby one allows the first M items to pass, and then selects the first later arriving item whose rank is either equal to or greater than the highest rank of the first M items (if such an item exists). Let denote the event that one selects an item of highest rank using strategy and let denote the corresponding probability. We obtain a formula for , and for , when , with . In the classical secretary problem (), the asymptotic probability of success using an optimal strategy is . For , the asymptotic probability of success using an optimal strategy from the above class is about 0.701. For , that probability already exceeds 0.99. In the problem with multiple items at each rank, there is an additional measure of efficiency of a strategy besides the probability of selecting an item of highest rank; namely how quickly one selects an item of highest rank. We give a rather complete picture of this efficiency.
期刊介绍:
Interdisciplinary in its coverage, Advances in Applied Mathematics is dedicated to the publication of original and survey articles on rigorous methods and results in applied mathematics. The journal features articles on discrete mathematics, discrete probability theory, theoretical statistics, mathematical biology and bioinformatics, applied commutative algebra and algebraic geometry, convexity theory, experimental mathematics, theoretical computer science, and other areas.
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