APPROXIMATING NONRENEWAL PROCESSES BY MARKOV-CHAINS - USE OF SUPER-ERLANG (SE) CHAINS
成果类型：
Article
署名作者：
BITRAN, GR; DASU, S
署名单位：
University of California System; University of California Los Angeles
刊物名称：
OPERATIONS RESEARCH
ISSN/ISSBN：
0030-364X
DOI：
10.1287/opre.41.5.903
发表日期：
1993
页码：
903-923
关键词：
摘要：
We study a class of point processes generated by transitions in Markov chains. We are primarily concerned with approximating superposed phase renewal processes by these point processes. We identify a subclass of Markov chains that we call Super-Erlang chains. These chains have special properties that facilitate the development of approximations. We outline an approximation procedure and provide computational results that demonstrate the potential of the approach. The primary motivation for this study is the analysis of open queueing networks.