Please use this identifier to cite or link to this item: https://doi.org/10.1109/WSC.2013.6721491
Title: Determining the optimal sampling set size for random search
Authors: Zhu, C.
Xu, J.
Chen, C.-H.
Lee, L.H. 
Hu, J.
Issue Date: 2013
Source: Zhu, C.,Xu, J.,Chen, C.-H.,Lee, L.H.,Hu, J. (2013). Determining the optimal sampling set size for random search. Proceedings of the 2013 Winter Simulation Conference - Simulation: Making Decisions in a Complex World, WSC 2013 : 1016-1024. ScholarBank@NUS Repository. https://doi.org/10.1109/WSC.2013.6721491
Abstract: Random search is a core component of many well known simulation optimization algorithms such as nested partition and COMPASS. Given a fixed computation budget, a critical decision is how many solutions to sample from a search area, which directly determines the number of simulation replications for each solution assuming that each solution receives the same number of simulation replications. This is another instance of the exploration vs. exploitation tradeoff in simulation optimization. Modeling the performance profile of all solutions in the search area as a normal distribution, we propose a method to (approximately) optimally determine the size of the sampling set and the number of simulation replications and use numerical experiments to demonstrate its performance. © 2013 IEEE.
Source Title: Proceedings of the 2013 Winter Simulation Conference - Simulation: Making Decisions in a Complex World, WSC 2013
URI: http://scholarbank.nus.edu.sg/handle/10635/87321
ISBN: 9781479939503
DOI: 10.1109/WSC.2013.6721491
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