Hierarchic Markov processes and their applications in replacement models

TY - JOUR

T1 - Hierarchic Markov processes and their applications in replacement models

AU - Kristensen, Anders R.

PY - 1988/1/1

Y1 - 1988/1/1

N2 - In this paper a new notion of a hierarchic Markov process is introduced. It is a series of Markov decision processes called subprocesses built together in one Markov decision process called the main process. The hierarchic structure is specially designed to fit replacement models which in the traditional formulation as ordinary Markov decision processes are usually very large. The basic theory of hierarchic Markov processes is described and examples are given of applications in replacement models. The theory can be extended to fit a situation where the replacement decision depends on the quality of the new asset available for replacement.

AB - In this paper a new notion of a hierarchic Markov process is introduced. It is a series of Markov decision processes called subprocesses built together in one Markov decision process called the main process. The hierarchic structure is specially designed to fit replacement models which in the traditional formulation as ordinary Markov decision processes are usually very large. The basic theory of hierarchic Markov processes is described and examples are given of applications in replacement models. The theory can be extended to fit a situation where the replacement decision depends on the quality of the new asset available for replacement.

KW - agriculture

KW - Management

KW - Markov decision programming

KW - optimization

KW - stochastic processes

UR - http://www.scopus.com/inward/record.url?scp=0024015934&partnerID=8YFLogxK

U2 - 10.1016/0377-2217(88)90031-8

DO - 10.1016/0377-2217(88)90031-8

M3 - Journal article

AN - SCOPUS:0024015934

SN - 0377-2217

VL - 35

SP - 207

EP - 215

JO - European Journal of Operational Research

JF - European Journal of Operational Research

IS - 2

ER -