The polling system with switch-over durations is a useful model with several practical applications. It is classified as a Discrete Event Dynamic System (DEDS) for which no one agreed upon modelling approach exists. Furthermore, DEDS are quite complex. To date, the most sophisticated approach to modelling the polling system of interest has been a Continuous-time Markov Decision Process (CTMDP). This paper presents a Semi-Markov Decision Process (SMDP) formulation of the polling system as to introduce additional modelling power. Such power comes at the expense of truncation errors and expensive numerical integrals which naturally leads to the question of whether the SMDP policy provides a worthwhile advantage. To further add to this scenario, it is shown how sparsity can be exploited in the CTMDP to develop a computationally efficient model. The discounted performance of the SMDP and CTMDP policies are evaluated using a Semi-Markov Process simulator. The two policies are accompanied by a heuristic policy specifically developed for this polling system a well as an exhaustive service policy. Parametric and non-parametric hypothesis tests are used to test whether differences in performance are statistically significant.
翻译:具有交接期的投票系统是一种有用的模式,有几种实际应用,被归类为无人同意的模型化方法的分立事件动态系统(DEDS),此外,DDS相当复杂,迄今为止,模拟投票系统最复杂的方法一直是持续时间的Markov决策程序(CTMDP),本文介绍了投票系统的半马尔科夫决策程序(SMDP)的制定,以引入额外的模拟力,这种权力是以截断错误和昂贵的数字组合为代价的,这自然导致SMDP政策是否提供有价值的优势的问题。为了进一步补充这一假设,可以说明CTMDP如何利用松散性来开发一个计算效率高的模式。SMDP和CTMDP政策的折扣性表现是通过一个半马尔科夫进程模拟器进行评估的。两种政策都伴有专门为这一投票系统制定的超常政策,以及一项详尽的服务政策。为了检验业绩差异是否具有统计意义,使用了参数和非参数假设测试。