Optimal strategy analysis of an N-policy M[x]/M/1 queueing system with a removable and non-reliable server

OPSEARCH ◽  
2008 ◽  
Vol 45 (1) ◽  
pp. 79-95 ◽  
Author(s):  
S. Anantha Lakshmi ◽  
M. I. Afthab Begum ◽  
S. Swaroopa Rani
Keyword(s):  
Optimal Strategy ◽  
Queueing System ◽  
Strategy Analysis

Optimal strategy analysis of an N-policy two-phase MX/M/1 queueing system with server startup and breakdowns

OPSEARCH ◽  
2011 ◽  
Vol 48 (2) ◽  
pp. 109-122 ◽  
Author(s):  
Vasanta Kumar Vemuri ◽  
Venkata Siva Nageswara Hari Prasad Boppana ◽  
Chandan Kotagiri ◽  
Ravi Teja Bethapudi
Keyword(s):  
Optimal Strategy ◽  
Queueing System ◽  
Two Phase ◽  
Strategy Analysis

Optimal Strategy Analysis of anN-Policy Two-PhaseMX/Ek/1 Queueing System with Server Startup and Breakdowns

2011 ◽  
Vol 8 (3) ◽  
pp. 285-301 ◽  
Author(s):  
V. Vasanta Kumar ◽  
K. Chandan ◽  
B. Ravi Teja ◽  
B.V.S.N. Hari Prasad
Keyword(s):  
Optimal Strategy ◽  
Queueing System ◽  
Strategy Analysis

Optimal Strategy in Queueing Systems in Emergency Department

2018 ◽  
Vol 13 (1) ◽  
pp. 69-80
Author(s):  
Zeng Hui ◽  
Tian Ruiling ◽  
Liu Yupeng ◽  
Hou Yumei
Keyword(s):  
Emergency Department ◽  
Optimal Strategy ◽  
Queue Length ◽  
Queueing System ◽  
Queueing Systems ◽  
Optimal Strategies ◽  
Game Problem ◽  
Noncooperative Game ◽  
Service Interruption ◽  
Urgent Patient

The authors' study a noncooperative game problem for queueing control in emergency department (ED). One of the challenges to emergency department (ED) is the control of the urgent patients and the non-urgent patients. The urgent patient which is the primary customer, can be considered as the service interruption in a queueing system. The service interruptions occur frequently and can incur significant delays for the non-urgent patients. Therefore, a non-urgent patient needs to decide whether to join the queue or leave. The scenario is modeled as an M/M/1 queueing game with server interruption where each patient wants to optimize his benefit. It is shown that the individually optimal strategy for joining the queue is characterized by a threshold of queue length. The socially optimal threshold of queue length is also obtained. To bridge the gap between the individually and socially optimal strategies, a pricing mechanism is proposed to toll the service of each non-urgent patient, thus equalizing the two optimal strategies.

Automated Development of Clinical Strategies Using Multistage Decision Analysis

1986 ◽  
Vol 25 (04) ◽  
pp. 207-214 ◽  
Author(s):  
P. Glasziou
Keyword(s):  
Decision Tree ◽  
Decision Analysis ◽  
Decision Trees ◽  
Optimal Strategy ◽  
Cholestatic Jaundice ◽  
Clinical Strategies ◽  
Simultaneous Study

SummaryThe development of investigative strategies by decision analysis has been achieved by explicitly drawing the decision tree, either by hand or on computer. This paper discusses the feasibility of automatically generating and analysing decision trees from a description of the investigations and the treatment problem. The investigation of cholestatic jaundice is used to illustrate the technique.Methods to decrease the number of calculations required are presented. It is shown that this method makes practical the simultaneous study of at least half a dozen investigations. However, some new problems arise due to the possible complexity of the resulting optimal strategy. If protocol errors and delays due to testing are considered, simpler strategies become desirable. Generation and assessment of these simpler strategies are discussed with examples.

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