Discrete-time queues with zero-regenerative arrivals: moments and examples

In this paper we investigate a single-server discrete-time queueing system with single-slot service times. The stationary ergodic arrival process this queueing system is subject to, satisfies a regeneration property when there are no arrivals during a slot. Expressions for the mean and the variance of the queue content in steady state are obtained for this broad class which includes among others autoregressive arrival processes and M/G/infinity-input or train arrival processes. To illustrate our results, we then consider a number of numerical examples

Data Systems Dynamic Simulator

The Data System Dynamic Simulator (DSDS) is a discrete event simulation tool. It was developed for NASA for the specific purpose of evaluating candidate architectures for data systems of the Space Station era. DSDS provides three methods for meeting this requirement. First, the user has access to a library of standard pre-programmed elements. These elements represent tailorable components of NASA data systems and can be connected in any logical manner. Secondly, DSDS supports the development of additional elements. This allows the more sophisticated DSDS user the option of extending the standard element set. Thirdly, DSDS supports the use of data streams simulation. Data streams is the name given to a technique that ignores packet boundaries, but is sensitive to rate changes. Because rate changes are rare compared to packet arrivals in a typical NASA data system, data stream simulations require a fraction of the CPU run time. Additionally, the data stream technique is considerably more accurate than another commonly-used optimization technique

A Retrieval Queueing Model With Feedback

A multi-server retrial queuing model with feedback is considered in this paper.Input flow of calls is modeled using a Markovian Arrival Process (M AP) and the service time is assumed to follow an exponential distribution. An arriving call enters into service should there be a free server. Otherwise, in accordance to Bernoulli trials, the call will enter into an infinite orbit (referred to as a retrial orbit) to retry along with other calls to get into service or will leave the system forever. After obtaining a service each call, independent of the others, will either enter into a finite orbit (referred to as a feedback orbit) for another service or leave the system forever. The decision to enter into the feedback orbit or not is done according to another Bernoulli trial. Calls from these two buffers will compete with the main source of calls based on signals received from two independent Poisson processes.The rates of these processes depend on the phase of the M AP. The steady-state analysis of the model is carried out and illustrative numerical examples including economical aspects are presented

Perceptionization of FM/FD/1 queuing model under various fuzzy numbers

We present a FM/FD/1 queuing model with unbounded limit under different fuzzy numbers. The arrival (landing) rate and service (administration) rate are thought to be fuzzy numbers such as triangular, trapezoidal and pentagonal fuzzy numbers. Because random event can only be observed in an uncertain manner, the fuzzy result of an uncertainty mapping is a fuzzy random variable. Consequently, it is conceivable to characterize the specific connection between randomness and fuzziness. The execution proportions of this lining miniature are fuzzified after that examined by utilizing α-cut estimations and DSW algorithm (Dong, Shah and Wong). Relating to different fuzzy numbers, the numerical precedents are delineated to test the attainability of this model (miniature). A comparative illustration corresponding to each fuzzy number is accomplished for various estimations of α

How stochasticity and emergencies disrupt the surgical schedule

In health care system, the operating theatre is recognized as having an important role, notably in terms of generated income and cost. Its management, and in particular its scheduling, is thus a critical activity, and has been the sub ject of many studies. However, the stochasticity of the operating theatre environment is rarely considered while it has considerable effect on the actual working of a surgical unit. In practice, the planners keep a safety margin, let’s say 15% of the capacity, in order to absorb the effect of unpredictable events. However, this safety margin is most often chosen sub jectively, from experience. In this paper, our goal is to rationalize this process. We want to give insights to managers in order to deal with the stochasticity of their environment, at a tactical–strategic decision level. For this, we propose an analytical approach that takes account of the stochastic operating times as well as the disruptions caused by emergency arrivals. From our model, various performance measures can be computed: the emergency disruption rate, the waiting time for an emergency, the distribution of the working time, the probability of overtime, the average overtime, etc. In particular, our tool is able to tell how many operations can be scheduled per day in order to keep the overtime limited.health care, surgical schedule, emergencies, Markov chain.

A survey on performance analysis of warehouse carousel systems

This paper gives an overview of recent research on the performance evaluation and design of carousel systems. We discuss picking strategies for problems involving one carousel, consider the throughput of the system for problems involving two carousels, give an overview of related problems in this area, and present an extensive literature review. Emphasis has been given on future research directions in this area