Matches in SemOpenAlex for { <https://semopenalex.org/work/W4386174927> ?p ?o ?g. }
- W4386174927 endingPage "111222" @default.
- W4386174927 startingPage "111222" @default.
- W4386174927 abstract "Many decision problems in modern industries involve the performance optimization of discrete-event dynamic systems. Because of the stochasticity of these systems, performance usually is evaluated through simulation. Finding the optimal designs of these systems can be modeled as a ranking and selection problem. This research considers the problem of selecting the best design from among numerous designs. We minimized the expected opportunity cost (EOC) of incorrect selection with a limited computing budget. The entire domain of designs could be divided into several adjacent partitions, and the performances of designs in each partition were estimated using a regression metamodel. We assumed the underlying function in each partition to be quadratic. Using large deviations theory, we then derived an asymptotically optimal budget allocation rule and developed a sequential allocation algorithm to implement the allocation rule. The EOC measure was compared with the probability of correct selection measure in a set of large-scale simulation optimization problems. Numerical experiments verified the effectiveness of our proposed simulation procedure." @default.
- W4386174927 created "2023-08-26" @default.
- W4386174927 creator A5007751109 @default.
- W4386174927 creator A5048553979 @default.
- W4386174927 creator A5066361885 @default.
- W4386174927 creator A5073973267 @default.
- W4386174927 date "2023-11-01" @default.
- W4386174927 modified "2023-10-14" @default.
- W4386174927 title "An efficient simulation procedure for the expected opportunity cost using metamodels" @default.
- W4386174927 cites W1536615069 @default.
- W4386174927 cites W1964031948 @default.
- W4386174927 cites W1972357824 @default.
- W4386174927 cites W1974898730 @default.
- W4386174927 cites W1977764678 @default.
- W4386174927 cites W2005751144 @default.
- W4386174927 cites W2015690348 @default.
- W4386174927 cites W2029376565 @default.
- W4386174927 cites W2029530218 @default.
- W4386174927 cites W2033484776 @default.
- W4386174927 cites W2037728958 @default.
- W4386174927 cites W2038266588 @default.
- W4386174927 cites W2040174083 @default.
- W4386174927 cites W2046282120 @default.
- W4386174927 cites W2065257837 @default.
- W4386174927 cites W2074339441 @default.
- W4386174927 cites W2098092309 @default.
- W4386174927 cites W2115799946 @default.
- W4386174927 cites W2118882248 @default.
- W4386174927 cites W2122470810 @default.
- W4386174927 cites W2142858180 @default.
- W4386174927 cites W2145286212 @default.
- W4386174927 cites W2484647765 @default.
- W4386174927 cites W2530493829 @default.
- W4386174927 cites W2601522716 @default.
- W4386174927 cites W2773271314 @default.
- W4386174927 cites W2794717456 @default.
- W4386174927 cites W2810447948 @default.
- W4386174927 cites W2883303788 @default.
- W4386174927 cites W2894084268 @default.
- W4386174927 cites W2897334107 @default.
- W4386174927 cites W2905058552 @default.
- W4386174927 cites W2912116206 @default.
- W4386174927 cites W2941322302 @default.
- W4386174927 cites W2952850261 @default.
- W4386174927 cites W2963076019 @default.
- W4386174927 cites W2963653944 @default.
- W4386174927 cites W2972635416 @default.
- W4386174927 cites W2973896077 @default.
- W4386174927 cites W2981862588 @default.
- W4386174927 cites W2995738133 @default.
- W4386174927 cites W3088744486 @default.
- W4386174927 cites W3139896449 @default.
- W4386174927 cites W3205730600 @default.
- W4386174927 cites W4212920552 @default.
- W4386174927 cites W4220878832 @default.
- W4386174927 cites W4233924148 @default.
- W4386174927 doi "https://doi.org/10.1016/j.automatica.2023.111222" @default.
- W4386174927 hasPublicationYear "2023" @default.
- W4386174927 type Work @default.
- W4386174927 citedByCount "0" @default.
- W4386174927 crossrefType "journal-article" @default.
- W4386174927 hasAuthorship W4386174927A5007751109 @default.
- W4386174927 hasAuthorship W4386174927A5048553979 @default.
- W4386174927 hasAuthorship W4386174927A5066361885 @default.
- W4386174927 hasAuthorship W4386174927A5073973267 @default.
- W4386174927 hasBestOaLocation W43861749271 @default.
- W4386174927 hasConcept C114614502 @default.
- W4386174927 hasConcept C119857082 @default.
- W4386174927 hasConcept C124101348 @default.
- W4386174927 hasConcept C126255220 @default.
- W4386174927 hasConcept C129844170 @default.
- W4386174927 hasConcept C147203929 @default.
- W4386174927 hasConcept C154945302 @default.
- W4386174927 hasConcept C189430467 @default.
- W4386174927 hasConcept C199360897 @default.
- W4386174927 hasConcept C2524010 @default.
- W4386174927 hasConcept C2780009758 @default.
- W4386174927 hasConcept C33923547 @default.
- W4386174927 hasConcept C41008148 @default.
- W4386174927 hasConcept C42812 @default.
- W4386174927 hasConcept C44154836 @default.
- W4386174927 hasConcept C49937458 @default.
- W4386174927 hasConcept C81917197 @default.
- W4386174927 hasConcept C86610423 @default.
- W4386174927 hasConceptScore W4386174927C114614502 @default.
- W4386174927 hasConceptScore W4386174927C119857082 @default.
- W4386174927 hasConceptScore W4386174927C124101348 @default.
- W4386174927 hasConceptScore W4386174927C126255220 @default.
- W4386174927 hasConceptScore W4386174927C129844170 @default.
- W4386174927 hasConceptScore W4386174927C147203929 @default.
- W4386174927 hasConceptScore W4386174927C154945302 @default.
- W4386174927 hasConceptScore W4386174927C189430467 @default.
- W4386174927 hasConceptScore W4386174927C199360897 @default.
- W4386174927 hasConceptScore W4386174927C2524010 @default.
- W4386174927 hasConceptScore W4386174927C2780009758 @default.
- W4386174927 hasConceptScore W4386174927C33923547 @default.
- W4386174927 hasConceptScore W4386174927C41008148 @default.
- W4386174927 hasConceptScore W4386174927C42812 @default.