Abstract
The aim of this paper is to combine the ability of fuzzy sets to represent practical situations with the well-known established traditional queuing approaches which are rigorous but the assumptions are frequently too far from reality. It is shown that this approach can utilize the advantages of both the fuzzy and probability approaches to make the model more realistic and less restrictive. Both α-cut sets and the use of random variables to represent fuzzy numbers are investigated. Trapezoidal fuzzy numbers are used and the analytical and simulation results are discussed based on actual examples.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
