TY - GEN
T1 - Approximately Optimal Computing-Budget Allocation for subset ranking
AU - Zhang, Junqi
AU - Li, Zezhou
AU - Wang, Cheng
AU - Zang, Di
AU - Zhou, Mengchu
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/6/29
Y1 - 2015/6/29
N2 - The best design among many can be selected through their accurate performance evaluation. When such evaluation is based on discrete event simulations, the design selection is extremely time-consuming. Ordinal optimization greatly speeds up this process. Optimal Computing-Budget Allocation (OCBA) has further accelerated it. Other kinds of OCBA have been introduced for reaching different goals, for example, to select the optimal subset of designs. However, facing the issue of subset ranking, which is a generalized form from problems selecting the best design or optimal subset, all the existing ones are insufficient. This work develops a new OCBA-based approach to address this subset ranking issue. Through mathematical deduction, its theoretical foundation is laid. Our numerical simulation results reveal that it indeed outperforms all the other existing methods in terms of probability of correct subset ranking and computational efficiency.
AB - The best design among many can be selected through their accurate performance evaluation. When such evaluation is based on discrete event simulations, the design selection is extremely time-consuming. Ordinal optimization greatly speeds up this process. Optimal Computing-Budget Allocation (OCBA) has further accelerated it. Other kinds of OCBA have been introduced for reaching different goals, for example, to select the optimal subset of designs. However, facing the issue of subset ranking, which is a generalized form from problems selecting the best design or optimal subset, all the existing ones are insufficient. This work develops a new OCBA-based approach to address this subset ranking issue. Through mathematical deduction, its theoretical foundation is laid. Our numerical simulation results reveal that it indeed outperforms all the other existing methods in terms of probability of correct subset ranking and computational efficiency.
KW - Discrete-event system
KW - Optimal computing-budget allocation (OCBA)
KW - Ranking and selection
UR - http://www.scopus.com/inward/record.url?scp=84938281616&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84938281616&partnerID=8YFLogxK
U2 - 10.1109/ICRA.2015.7139736
DO - 10.1109/ICRA.2015.7139736
M3 - Conference contribution
AN - SCOPUS:84938281616
T3 - Proceedings - IEEE International Conference on Robotics and Automation
SP - 3856
EP - 3861
BT - 2015 IEEE International Conference on Robotics and Automation, ICRA 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2015 IEEE International Conference on Robotics and Automation, ICRA 2015
Y2 - 26 May 2015 through 30 May 2015
ER -