In this paper, equilibrium strategies and optimal balking strategies of customers in a constant retrial queue with multiple vacations and the N-policy under two information levels, respectively, are investigated. We assume that there is no waiting area in front of the server and an arriving customer is served immediately if the server is idle; otherwise (the server is either busy or on a vacation) it has to leave the system to join a virtual retrial orbit waiting for retrials according to the FCFS rules. After a service completion, if the system is not empty, the server becomes idle, available for serving the next customer, either a new arrival or a retried customer from the virtual retrial orbit; otherwise (if the system is empty), the server starts a vacation. Upon the completion of a vacation, the server is reactivated only if it finds at least N customers in the virtual orbit; otherwise, the server continues another vacation. We study this model at two levels of information, respectively. For each level of information, we obtain both equilibrium and optimal balking strategies of customers, and make corresponding numerical comparisons. Through Particle Swarm Optimization (PSO) algorithm, we explore the impact of parameters on the equilibrium and social optimal thresholds, and obtain the trend in changes, as a function of system parameters, for the optimal social welfare, which provides guiding significance for social planners. Finally, by comparing the social welfare under two information levels, we find that whether the system information should be disclosed to customers depends on how to maintain the growth of social welfare.
针对非正态响应的部分因子试验,当筛选试验所涉及的因子数目较大时,提出了基于广义线性模型(generalized linear models,GLM)的贝叶斯变量与模型选择方法.首先,针对模型参数的不确定性,选择了经验贝叶斯先验.其次,在广义线性模型的线性预测器中对每个变量设置了二元变量指示器,并建立起变量指示器与模型指示器之间的转换关系.然后,利用变量指示器与模型指示器的后验概率来识别显著性因子与选择最佳模型.最后,以实际的工业案例说明此方法能够有效地识别非正态响应部分因子试验的显著性因子. 相似文献
This study assesses the risk/return profile of three market timing strategies namely traditional, bull and bear timing under different market conditions on the Johannesburg Stock Exchange.The results indicate that market timing does lead to a lower variability of returns than a buy-and-hold strategy. On a risk-adjusted basis the required forecasting ability necessary to outperform the market is lower than previously thought. Under bearish conditions a random guess is expected to yield returns above the risk-adjusted market return regardless of the timing strategy employed. 相似文献