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A system is \u201cin (not in) \u0393\u201d if the vector of the means is in (not in) \u0393, where the means must be estimated using Monte Carlo simulation. We develop algorithms for classifying the systems with a user-specified level of confidence using the minimum number of simulation replications so the probability of correct classification over all\n            <jats:italic>r<\/jats:italic>\n            systems satisfies a user-specified minimum value. Once the analyst provides prior values for the means and standard deviations of the random variables in each system, an initial number of simulation replications is performed to obtain current estimates of the means and standard deviations to assess whether the systems can be classified with the desired level of confidence. For any system that cannot be classified, heuristics are proposed to determine the number of additional simulation replications that would enable correct classification. Our contributions include the introduction of intuitive algorithms that are not only easy to implement, but also effective with their performance. Compared to other feasibility determination approaches, they also appear to be competitive. While the algorithms were initially developed in settings where system variance is assumed to be known and the random variables are independent, their performance remains satisfactory when those assumptions are relaxed.\n          <\/jats:p>","DOI":"10.1145\/3426359","type":"journal-article","created":{"date-parts":[[2021,1,8]],"date-time":"2021-01-08T18:43:10Z","timestamp":1610131390000},"page":"1-25","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["Novel Approaches to Feasibility Determination"],"prefix":"10.1145","volume":"31","author":[{"given":"Daniel","family":"Solow","sequence":"first","affiliation":[{"name":"Case Western Reserve University, Cleveland, OH, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Roberto","family":"Szechtman","sequence":"additional","affiliation":[{"name":"Naval Postgraduate School, Monterey, CA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Enver","family":"Y\u00fccesan","sequence":"additional","affiliation":[{"name":"INSEAD, Ayer Rajah Avenue, Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2021,1,8]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.5555\/1162708.1162833"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1002\/nav.20422"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/1842713.1842716"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/9.855560"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.5555\/767778.769032"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1287\/ijoc.1090.0327"},{"key":"e_1_2_1_7_1","doi-asserted-by":"crossref","unstructured":"A. Dembo and O. Zeitouni. 1998. Large deviations techniques and applications. In Applications of Mathematics Stochastic Modeling and Applied Probabaility. Volume 38. Springer-Verlag New York.  A. Dembo and O. Zeitouni. 1998. Large deviations techniques and applications. In Applications of Mathematics Stochastic Modeling and Applied Probabaility. Volume 38. Springer-Verlag New York.","DOI":"10.1007\/978-1-4612-5320-4"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1137\/070693424"},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/TAC.2016.2538466"},{"key":"e_1_2_1_10_1","doi-asserted-by":"crossref","unstructured":"A. Gelman J. B. Carlin H. S. Stern D. B. Dunson A. Vehtari and D. B. Rubin. 2013. Bayesian Data Analysis (3rd ed.). CRC Press Boca Raton FL.  A. Gelman J. B. Carlin H. S. Stern D. B. Dunson A. Vehtari and D. B. Rubin. 2013. Bayesian Data Analysis (3rd ed.). 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In Design of Experiments -- Ranking and Selection: Essays in Honor of Robert E. Bechhoffer T. J. Santner and A. C. Tamhane (Eds.). Marcel-Dekker New York 179--198."},{"key":"e_1_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.5555\/3042094.3042170"},{"key":"e_1_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejor.2005.10.041"},{"key":"e_1_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.5555\/1516744.1516803"},{"key":"e_1_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.5555\/3042094.3042203"},{"key":"e_1_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1287\/mnsc.29.10.1209"},{"key":"e_1_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.5555\/316731"},{"key":"e_1_2_1_23_1","volume-title":"Introduction to the non-asymptotic analysis of random matrices. Arxiv Preprint Arxiv:1011.3027","author":"Vershynin R.","year":"2010","unstructured":"R. Vershynin . 2010. Introduction to the non-asymptotic analysis of random matrices. Arxiv Preprint Arxiv:1011.3027 ( 2010 ). R. 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