{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,8]],"date-time":"2025-12-08T22:03:31Z","timestamp":1765231411446,"version":"3.46.0"},"reference-count":21,"publisher":"World Scientific Pub Co Pte Ltd","issue":"06","funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["72091211"],"award-info":[{"award-number":["72091211"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Asia Pac. J. Oper. Res."],"published-print":{"date-parts":[[2025,12]]},"abstract":"<jats:p>Robust ranking and selection (R&amp;S) is an important and challenging variation of the conventional R&amp;S that seeks to select the best alternative among a finite set of alternatives. It captures the common input uncertainty in the simulation model by using an ambiguity set to include multiple possible input distributions and shifts to select the best alternative with the smallest worst-case mean performance over the ambiguity set. In this paper, we aim at developing new fixed-budget robust R&amp;S procedures to minimize the probability of incorrect selection (PICS) under a limited sampling budget. Inspired by an additive upper bound of the PICS, we derive a new asymptotically optimal solution to the budget allocation problem. Accordingly, we design a new sequential optimal computing budget allocation (OCBA) procedure to solve robust R&amp;S problems efficiently. We then conduct a comprehensive numerical study to verify the superiority of our robust OCBA procedure over the existing ones. The numerical study also provides insights on the budget allocation behaviors that lead to enhanced efficiency.<\/jats:p>","DOI":"10.1142\/s0217595925400032","type":"journal-article","created":{"date-parts":[[2025,4,20]],"date-time":"2025-04-20T22:50:07Z","timestamp":1745189407000},"source":"Crossref","is-referenced-by-count":1,"title":["New Additive OCBA Procedures for Robust Ranking and Selection"],"prefix":"10.1142","volume":"42","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-9506-3238","authenticated-orcid":false,"given":"Yuchen","family":"Wan","sequence":"first","affiliation":[{"name":"School of Data Science, Fudan University 220 Handan Road, Shanghai 200433, P. R. China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-8984-539X","authenticated-orcid":false,"given":"Zaile","family":"Li","sequence":"additional","affiliation":[{"name":"Technology & Operations Management Area, INSEAD, Boulevard de Constance, 77305 Fontainebleau, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7011-4001","authenticated-orcid":false,"given":"L.","family":"Jeff Hong","sequence":"additional","affiliation":[{"name":"Department of Industrial and Systems Engineering, University of Minnesota, 207 Church Street SE, Minneapolis, MN 55455, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2025,4,21]]},"reference":[{"key":"S0217595925400032BIB001","doi-asserted-by":"publisher","DOI":"10.1142\/S0217595916500093"},{"key":"S0217595925400032BIB002","doi-asserted-by":"publisher","DOI":"10.1007\/s101070100286"},{"key":"S0217595925400032BIB003","series-title":"System Engineering and Operations Research","volume-title":"Stochastic Simulation Optimization: An Optimal Computing Budget Allocation","volume":"1","author":"Chen CH","year":"2011"},{"key":"S0217595925400032BIB004","doi-asserted-by":"publisher","DOI":"10.1023\/A:1008349927281"},{"key":"S0217595925400032BIB005","doi-asserted-by":"publisher","DOI":"10.1109\/WSC.2013.6721478"},{"key":"S0217595925400032BIB006","doi-asserted-by":"publisher","DOI":"10.1287\/mnsc.2018.3213"},{"key":"S0217595925400032BIB007","doi-asserted-by":"publisher","DOI":"10.1109\/WSC.2016.7822146"},{"key":"S0217595925400032BIB008","doi-asserted-by":"publisher","DOI":"10.1016\/j.automatica.2017.03.019"},{"key":"S0217595925400032BIB009","doi-asserted-by":"publisher","DOI":"10.1007\/s42524-021-0152-6"},{"key":"S0217595925400032BIB010","doi-asserted-by":"publisher","DOI":"10.1016\/S0927-0507(06)13017-0"},{"key":"S0217595925400032BIB011","doi-asserted-by":"publisher","DOI":"10.1016\/j.automatica.2023.111042"},{"key":"S0217595925400032BIB012","doi-asserted-by":"crossref","unstructured":"Liu, X, Y Peng, G Zhang and R Zhou (2023). An efficient node selection policy for Monte Carlo tree search with neural networks. Working Paper. http:\/\/dx.doi.org\/10.2139\/ssrn.4450999.","DOI":"10.2139\/ssrn.4450999"},{"key":"S0217595925400032BIB013","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-64182-9_5"},{"issue":"2","key":"S0217595925400032BIB014","first-page":"562","volume":"67","author":"Song E","year":"2019","journal-title":"Operations Research"},{"key":"S0217595925400032BIB015","doi-asserted-by":"publisher","DOI":"10.1109\/WSC.2015.7408183"},{"key":"S0217595925400032BIB016","doi-asserted-by":"publisher","DOI":"10.1109\/WSC60868.2023.10407226"},{"key":"S0217595925400032BIB017","unstructured":"Wu, D and E Zhou (2018). Analyzing and provably improving fixed budget ranking and selection algorithms. Preprint, arXiv:1811.12183 [math.OC]."},{"key":"S0217595925400032BIB018","doi-asserted-by":"publisher","DOI":"10.1142\/S0217595915500190"},{"key":"S0217595925400032BIB019","doi-asserted-by":"publisher","DOI":"10.1109\/WSC.2016.7822139"},{"key":"S0217595925400032BIB020","unstructured":"Zhang, Z and Y Peng (2024). Sample-efficient clustering and conquer procedures for parallel large-scale ranking and selection. Preprint, arXiv:2402.02196 [stat.ME]."},{"key":"S0217595925400032BIB021","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-64182-9_11"}],"container-title":["Asia-Pacific Journal of Operational Research"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S0217595925400032","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,8]],"date-time":"2025-12-08T09:12:01Z","timestamp":1765185121000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/10.1142\/S0217595925400032"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,4,21]]},"references-count":21,"journal-issue":{"issue":"06","published-print":{"date-parts":[[2025,12]]}},"alternative-id":["10.1142\/S0217595925400032"],"URL":"https:\/\/doi.org\/10.1142\/s0217595925400032","relation":{},"ISSN":["0217-5959","1793-7019"],"issn-type":[{"type":"print","value":"0217-5959"},{"type":"electronic","value":"1793-7019"}],"subject":[],"published":{"date-parts":[[2025,4,21]]},"article-number":"2540003"}}