Comparison of Fuzzy Queue Models

Abstract

Queuing theory is the study and modeling of people who wait in lines. Uncertainty is created when fuzziness gravels a perplexing item in regard to hazy information. Queuing systems are used in a wide range of daily contexts, including media transmission systems, computer networks, industrial firms, traffic control, organizations, and other industries and halls of fame. The M/M/1 and M/M/2 fuzzy queue models are compared in the extended scenario. Rate of Arrival andrate of service are taking Fuzzy numbers in triangular form. In order to quantify performance in queuing systems, this study proposes a technique for building the membership function utilizing DSW algorithms. An example is provided to compare the model's validity.