Simulation budget allocation for further enhancing the efficiency of ordinal optimization
Simulation budget allocation for further enhancing the efficiency of ordinal optimization
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DOI：
10.1023/a:1008349927281
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发表时间：
2000-07-01
影响因子：
2
通讯作者：
Chick, SE
中科院分区：
文献类型：
--
作者：
Chen, CH;Lin, JW;Chick, SE
有序优化作为一种有效的仿真和优化技术已经出现。在许多情况下可以实现指数收敛率。在本文中，我们提出了一种新的方法，可以进一步提高有序优化的效率。我们的方法确定了高效的模拟复制或样本数量，并显着降低了总模拟成本。我们还比较了几种不同的分配程序，包括模拟文献中流行的两阶段程序。数值测试表明，该方法比所有比较方法都要有效得多。结果进一步表明，我们的方法可以获得大于20的加速因子，超过使用顺序优化获得的210设计示例的加速因子。
Ordinal Optimization has emerged as an efficient technique for simulation and optimization. Exponential convergence rates can be achieved in many cases. In this paper, we present a new approach that can further enhance the efficiency of ordinal optimization. Our approach determines a highly efficient number of simulation replications or samples and significantly reduces the total simulation cost. We also compare several different allocation procedures, including a popular two-stage procedure in simulation literature. Numerical testing shows that our approach is much more efficient than all compared methods. The results further indicate that our approach can obtain a speedup factor of higher than 20 above and beyond the speedup achieved by the use of ordinal optimization for a 210-design example.