An Interpretation of Non-Preemptive Priority Fuzzy Queuing Model with Asymmetrical Service Rates

This paper presents Non-Preemptive priority fuzzy queuing model with asymmetrical service rates. Arrival rate and service rate are taken to be hexagonal, heptagonal, and octagonal fuzzy numbers. Here an interpretation is given to determine the performance measures by applying a new ranking technique through which the fuzzy values are reduced to the crisp values. This ranking technique has the benefit of being precise and relevant compared to other methods such as alpha-cut method and LR method. The main intention is to evaluate the fuzziness before the performance measures are processed by utilizing the regular queueing hypothesis. Three numerical examples are exhibited to show the validity implementation of the methodology.

An Improved Queuing Model for Reducing Average Waiting Time of Emergency Surgical Patients Using Preemptive Priority Scheduling

Our research objective is to reduce the Average Waiting Time for patients in an Emergency Department of public sector hospital. We have based our model on M/M/s Queuing System, our study revealssignificant findings on arrival rate of patients. During this simulation, we have used a preemptive priority scheduling model. In our practice, the arrival rate followed a Poisson distribution, averaging 30 patients per hour, with the Mean Service time of1.5 hours and Average Waiting Time recorded around 12.13 minutes. This research offersvaluable help to achieve better time management in emergency departments of high-density medical facilities.

Analysis of Fuzzy Non-preemptive Priority Queuing Model with Unequal Service Rate

This article provides an effective method to analyze the performance measures of non-preemptive fuzzy priority queues with unequal service rates. Here the arrival rate and the service rate are in fuzzy numbers. Using a new ranking method, the fuzzy values are reduced to the crisp values. For that cause, both the Triangular Fuzzy Number (TFN) and Trapezoidal Fuzzy Number (TpFN) are chosen to establish the proposal's effectiveness. An illustration is given to find the efficiency of the performance measures of the fuzzy queuing model.