EconPapers    
Economics at your fingertips  
 

Matrix-Analytic Methods – An Algorithmic Approach to Stochastic Modelling and Analysis

Qi-Ming He ()
Additional contact information
Qi-Ming He: University of Waterloo

A chapter in Optimization in Large Scale Problems, 2019, pp 41-45 from Springer

Abstract: Abstract The field of matrix analytic methods (MAM) was pioneered by Dr. Marcel F. Neuts in the middle of the 1970s for the study of queueing models. In the past 40 years, the theory on MAM has been advanced in parallel with its applications significantly. Matrix-analytic methods contain a set of tools fundamental to the analysis of a family of Markov processes rich in structure and of wide applicability. Matrix-analytic methods are extensively used in science, engineering, and statistics for the modelling, performance analysis, and design of computer systems, telecommunication networks, network protocols, manufacturing systems, supply chain management systems, risk/insurance models, etc.

Date: 2019
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:spochp:978-3-030-28565-4_8

Ordering information: This item can be ordered from
http://www.springer.com/9783030285654

DOI: 10.1007/978-3-030-28565-4_8

Access Statistics for this chapter

More chapters in Springer Optimization and Its Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-04-01
Handle: RePEc:spr:spochp:978-3-030-28565-4_8