Donghai He
George Mason University
7 Papers
2 Citations
Donghai He is an academic researcher from George Mason University. The author has contributed to research in topics: Ordinal optimization & Stochastic simulation. The author has an hindex of 5, co-authored 7 publications.
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Papers
Efficient Simulation Budget Allocation for Selecting an Optimal Subset
TL;DR: Preliminary numerical results indicate that the proposed new procedure has the potential to enhance computational efficiency for simulation optimization and the resulting allocations are superior to other methods in the literature that are tested, and the relative efficiency increases for larger problems.
290
Simulation optimization using the cross-entropy method with optimal computing budget allocation
TL;DR: Numerical experiments indicate that the computational efficiency of the CE method can be substantially improved if the ideas of computing budget allocation are applied, and the proposed approach improves the updating of the sampling distribution by carrying out this Computing budget allocation in an efficient manner.
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Efficient Dynamic Simulation Allocation in Ordinal Optimization
TL;DR: Investigation of the efficiency gains of using dynamic simulation allocation for ordinal optimization by comparing the sequential version of the optimal computing budget allocation method with optimal static and one-step look-ahead dynamic allocation schemes with "perfect information" on the sampling distribution indicates that the advantage of sequential allocation often outweighs having accurate estimates of the means and variances in determining a good simulation budget allocation.
65
Intelligent simulation for alternatives comparison and application to air traffic management
Chun-Hung Chen,Donghai He +1 more
TL;DR: A new and more general OCBA scheme is presented which can consider cases that users are interested not only the best design, but also any one in a good design set and the application of the OCBA to a design problem in US air traffic management is presented.