Erlang Loss Formulas: An Elementary Derivation
dc.contributor.author | Sarkar, Jyotirmoy | |
dc.contributor.department | Mathematical Sciences, School of Science | en_US |
dc.date.accessioned | 2023-03-10T21:16:25Z | |
dc.date.available | 2023-03-10T21:16:25Z | |
dc.date.issued | 2021-08 | |
dc.description.abstract | The celebrated Erlang loss formulas, which express the probability that exactly j of c available channels/servers are busy serving customers, were discovered about 100 years ago. Today we ask: “What is the simplest proof of these formulas?” As an alternative to more advanced methods, we derive the Erlang loss formulas using (1) an intuitive limit theorem of an alternating renewal process and (2) recursive relations that are solved using mathematical induction. Thus, we make the Erlang loss formulas comprehensible to beginning college mathematics students. We illustrate decision making in some practical problems using these formulas and other quantities derived from them. | en_US |
dc.eprint.version | Author's manuscript | en_US |
dc.identifier.citation | Sarkar, J. (2021). Erlang Loss Formulas: An Elementary Derivation. In B. K. Sinha & Md. N. H. Mollah (Eds.), Data Science and SDGs: Challenges, Opportunities and Realities (pp. 165–176). Springer. https://doi.org/10.1007/978-981-16-1919-9_14 | en_US |
dc.identifier.issn | 9789811619182 9789811619199 | en_US |
dc.identifier.uri | https://hdl.handle.net/1805/31834 | |
dc.language.iso | en_US | en_US |
dc.publisher | Springer | en_US |
dc.relation.isversionof | 10.1007/978-981-16-1919-9_14 | en_US |
dc.relation.journal | Data Science and SDGs: Challenges, Opportunities and Realities | en_US |
dc.rights | Publisher Policy | en_US |
dc.source | Author | en_US |
dc.subject | Alternating renewal process | en_US |
dc.subject | Ergodicity | en_US |
dc.subject | Semi-Markov process | en_US |
dc.subject | Queuing system | en_US |
dc.title | Erlang Loss Formulas: An Elementary Derivation | en_US |
dc.type | Article | en_US |