Title :
Markov chain with fuzzy states: Application to queuing decision models
Author :
de la Fuente, D. ; Pardo, M.J.
Author_Institution :
Dept. of Accounting & Bus. Adm., Oviedo Univ., Gijon, Spain
Abstract :
In this paper, we design a queuing system by calculating the best policy to be implemented regarding publicity decisions by using Markov chains with fuzzy states. To this end, first we calculate the steady-state probabilities when the states of the Markov Chain become fuzzy, and next we illustrate by an example the theoretical results previously obtained. In the example, we apply the linear programming solution to the Markovian decision process.
Keywords :
Markov processes; decision making; decision theory; fuzzy set theory; probability; queueing theory; Markov chain; fuzzy state; queuing decision model; steady-state probability; Computational complexity; Costs; Dynamic programming; Fuzzy sets; Fuzzy systems; Joining processes; Linear programming; Probability; Queueing analysis; Steady-state; Fuzzy sets; Markov chain; queuing theory;
Conference_Titel :
Industrial Engineering and Engineering Management, 2008. IEEM 2008. IEEE International Conference on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-2629-4
Electronic_ISBN :
978-1-4244-2630-0
DOI :
10.1109/IEEM.2008.4737854
