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Optimal computing budget allocation : ウィキペディア英語版 | Optimal computing budget allocation
Optimal computing budget allocation (OCBA) is a concept first introduced in the mid 1990s by Dr Chun-Hung Chen. This approach intends to maximize the overall simulation efficiency for finding an optimal decision.〔Fu, M, C. H. Chen, and L. Shi, “Some Topics for Simulation Optimization,” Proceedings of 2008 Winter Simulation Conference, pp. 27–38, Miami, FL, December 2008.〕 Simply put, OCBA is an approach to simulation that will help determine the number of replication and/or the simulation time that is needed in order to receive acceptable/best results within a set of given parameters.〔Chen, and Loo H. Lee. Stochastic simulation optimization an optimal computing budget allocation. Singapore Hackensack, NJ: World Scientific, 2011. Print..〕 This is accomplished by using an asymptotic framework to analyze the structure of the optimal allocation.〔Chen, C. H. "An Effective Approach to Smartly Allocate Computing Budget for Discrete Event Simulation," Proceedings of the 34th IEEE Conference on Decision and Control, pp. 2598–2605, December 1995.〕 == Intuitive explanations ==
OCBA’s goal is to provide a systematic approach to run a large number of simulations including only the critical alternatives in order to select the best alternative. In other words, focusing on only part the most critical alternatives, which minimizes computation time and reduces these critical estimators’ variances. The expected result maintains the required level of accuracy, while requiring less amount of work. For example we can create a simple simulation between 5 alternatives. The goal is to select an alternative with minimum average delay time. The figure below shows preliminary simulation results ( i.e. having run only a fraction of the required number of simulation replications). It is clear to see that alternative 2 and 3 have a significantly lower delay time ( highlighted in red). In order to save computation cost (which is time, resources and money spend on the process of running the simulation) OCBA suggests that more replications are required for alternative 2 and 3, and simulation can be stopped for 1, 4, and 5 much earlier without compromising results.
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