Analyzation Of Extended Tri-Cum Biseries Queuing Model In A Fuzzy Environment

Abstract

Queuing theory is the study and modelling of people who wait in lines. Fuzziness gravels a puzzling piece in relation to hazy info to produce uncertainty. A variety of varied daily situations, including media transmission systems, computer networks, manufacturing companies, traffic control, organizations and other fields and halls of fame, use queuing systems. In this extended queuing paradigm, three servers are linked in parallel in a tri cum biseries approach, which is analogous to a common place server in series. Arrivals are made in predefined batch sizes, according to the poison technique. Services are provided on a first-come, first-served basis. A generating function was used to calculate the steady state solutions and queue characteristics. There are numerous ways that can be used to address the issue of fuzzy numbers. We recommend utilizing the Wingspans ranking approach to identify the performance metrics of the provided queuing model. This wingspans ranking method converts arrival and service rate data into accurate numbers. The models' utility is proven using numerical examples.