Efficiency of the Antithetic Variate Method for Simulating Stochastic Networks
研究对偶变量法在估计随机网络完工时间期望时的效率，通过理论分析和实验表明，该方法平均只需蒙特卡洛模拟1/4的计算量即可达到相同精度，对称分布时甚至低于1/10。
This paper investigates the efficiency of antithetic variate simulation for estimating the expected completion time of stochastic networks. The method is compared with Monte Carlo simulation and considers both computation effort and the variance of the estimators. An efficiency ratio is first developed and then investigated within a theoretical framework. We then provide analytical proof of the superiority of the antithetic variate method for some networks whose activity durations are distributed symmetrically about their means. Next, experimental analysis of the efficiency ratio is carried out using test networks that are randomly structured and whose activity distributions are randomly assigned. The study shows that on the average the antithetic variate method can provide the same precision as Monte Carlo simulation, but with approximately 1/4 the computation effort. Furthermore, when activity distributions are symmetric, we can expect the antithetic variate method to require less than 1/10 the computation effort.