EVALUATING MULTI SERVER QUEUING SYSTEM EFFICIENCY: A COMPARATIVE STUDY BETWEEN FUZZY QUEUING MODEL AND INTUITIONISTIC FUZZY QUEUING MODEL WITH INFINITE CAPACITY CONSTRAINTS

In this study, we suggest an innovative analytical approach employing triangular fuzzy and triangular intuitionistic fuzzy numbers to ascertain the membership functions governing significant service-execution proportions within multiserver queuing models. Departing from conventional methodologies, both the inter-entry and completion rates are characterized by fuzzy natures, introducing a novel dimension to the analysis. Through numerical validation, our model demonstrates viability in the multiserver queuing context, bolstering its credibility. Furthermore, we conduct a contextual investigation, juxtaposing individual fuzzy metrics, thereby revealing the superior categorization potential of intuitionistic fuzzy queuing models over their fuzzy counterparts. Expanding the horizons of traditional fuzzy queuing theory, our integration of intuitionistic fuzzy environments promises enhanced queuing model implementation efficacy. Our primary objective lies in evaluating the productivity of a multi-server queuing model with limitless capacity, leveraging both fuzzy queuing and intuitionistic fuzzy queuing theories. Embracing a framework where arrival and service rates are characterized by triangular and intuitionistic triangular fuzzy numbers, we undertake a thorough assessment to establish evaluation criteria, adhering to a design protocol that preserves fuzzy values without converting them into crisp values. Additionally, we address two statistical challenges to ascertain the method's validity.