Using discrete event simulation to fit probability distributions for autocorrelated service times

Warning The system is temporarily closed to updates for reporting purpose.

Araghi, Mojtaba and Balcıoğlu, Barış (2020) Using discrete event simulation to fit probability distributions for autocorrelated service times. INFOR: Information Systems and Operational Research, 58 (1). pp. 124-140. ISSN 0315-5986 (Print) 1916-0615 (Online)

This is the latest version of this item.

[thumbnail of araghi_balcioglu.pdf] PDF
araghi_balcioglu.pdf
Restricted to Repository staff only

Download (277kB) | Request a copy

Abstract

In the literature, it has been shown that autocorrelation in service times has a dramatic impact on performance measures in delay systems. Although some studies deal with systems having autocorrelated service times, a general renewal approximation methodology that can incorporate this information in analytical models has not been previously proposed. In this paper, we develop a discrete event simulation based analytical method to fit approximating distributions to capture the characteristics of autocorrelated service times. Our observations indicate that a single approximating service time distribution fails to accurately predict the behaviour of the delay system. Therefore, we include the server utilization information in the developed method, which, in turn, provides a family of approximating service times. Testing our approximation both in predicting the mean delay and the system size distribution of the original systems with autocorrelated service times proves that it is highly accurate.
Item Type: Article
Uncontrolled Keywords: Autocorrelation, index of dispersion, mean waiting time, queueing, make-to-stock queues
Subjects: Q Science > QA Mathematics > QA273-280 Probabilities. Mathematical statistics
Divisions: Faculty of Engineering and Natural Sciences > Academic programs > Industrial Engineering
Faculty of Engineering and Natural Sciences
Depositing User: Barış Balcıoğlu
Date Deposited: 12 May 2020 13:17
Last Modified: 04 Aug 2023 20:03
URI: https://research.sabanciuniv.edu/id/eprint/39890

Available Versions of this Item

Actions (login required)

View Item
View Item