Queueing theory: Difference between revisions

Content deleted Content added
Undid revision 1185791106 by Sydney.Grace.H (talk); seems like original research: mostly unsourced analysis, some sourcing to blogs, tutorial tone
Added some background and additional information.
Line 26:
| url-status = live
}}</ref><ref>{{cite book |url= https://openaccess.city.ac.uk/id/eprint/2309/ |archive-url= https://web.archive.org/web/20210907100556/https://openaccess.city.ac.uk/id/eprint/2309/ |url-status= dead |archive-date= September 7, 2021 |access-date= 2008-05-20 |author= Mayhew, Les |author2= Smith, David |date= December 2006 |title= Using queuing theory to analyse completion times in accident and emergency departments in the light of the Government 4-hour target |publisher= [[Cass Business School]] |isbn= 978-1-905752-06-5 }}</ref>
 
Queueing theory is one of the major areas of study in the discipline of management science. Through management science, businesses are able to solve a variety of problems using different scientific and mathematical approaches. Queueing analysis is the probabilistic analysis of waiting lines, and thus the results, also referred to as the operating characteristics, are probabilistic rather than deterministic.<ref>{{Cite book |last=Taylor |first=Bernard W. |title=Introduction to management science |date=2019 |publisher=Pearson |isbn=978-0-13-473066-0 |edition=13th edition |location=New York, NY}}</ref> The probability that n customers are in the queueing system, the average number of customers in the queueing system, the average number of customers in the waiting line, the average time spent by a customer in the total queuing system, the average time spent by a customer in the waiting line, and finally the probability that the server is busy or idle are all of the different operating characteristics that these queueing models compute.<ref>{{Cite book |last=Taylor |first=Bernard W. |title=Introduction to management science |date=2019 |publisher=Pearson |isbn=978-0-13-473066-0 |edition=13th edition |location=New York, NY}}</ref> The overall goal of queueing analysis is to compute these characteristics for the current system and then test several alternatives that could lead to improvement. Computing the operating characteristics for the current system and comparing the values to the characteristics of the alternative systems allows managers to see the pros and cons of each potential option. These systems help in the final decision making process by showing ways to increase savings, reduce waiting time, improve efficiency, etc. The main queueing models that can be used are the single-server waiting line system and the multiple-server waiting line system, which are discussed further below. These models can be further differentiated depending on whether service times are constant or undefined, the queue length is finite, the calling population is finite, etc. <ref>{{Cite book |last=Taylor |first=Bernard W. |title=Introduction to management science |date=2019 |publisher=Pearson |isbn=978-0-13-473066-0 |edition=13th edition |location=New York, NY}}</ref>
 
== Spelling ==