Optimal Dynamic Outpatient Scheduling for a Diagnostic Facility With Two Waiting Time Targets

2016 ◽  
Vol 61 (12) ◽  
pp. 3725-3739 ◽  
Author(s):  
Na Geng ◽  
Xiaolan Xie
2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Koichi Nakade ◽  
Hiroki Niwa

In a manufacturing and inventory system, information on production and order lead time helps consumers’ decision whether they receive finished products or not by considering their own impatience on waiting time. In Savaşaneril et al. (2010), the optimal dynamic lead time quotation policy in a one-stage production and inventory system with a base stock policy for maximizing the system’s profit and its properties are discussed. In this system, each arriving customer decides whether he/she enters the system based on the quoted lead time informed by the system. On the other hand, the customer’s utility may be small under the optimal quoted lead time policy because the actual lead time may be longer than the quoted lead time. We use a utility function with respect to benefit of receiving products and waiting time and propose several kinds of heuristic lead time quotation policies. These are compared with optimal policies with respect to both profits and customer’s utilities. Through numerical examples some kinds of heuristic policies have better expected utilities of customers than the optimal quoted lead time policy maximizing system’s profits.


2020 ◽  
Author(s):  
Line Flytkjær Virgilsen ◽  
Line Hvidberg ◽  
Peter Vedsted

Abstract Background: Research indicate that when general practitioners (GPs) refer their patients for specialist care, the patient often has long distance. This study had a twofold aim: in accordance to the GP’s suspicion of cancer, we investigated the association between: 1) cancer patient’s travel distance to the first specialised diagnostic facility and the GP’s diagnostic strategy and 2) cancer patient’s travel distance to the first specialised diagnostic facility and satisfaction with the waiting time and the availability of diagnostic investigations.Method: This combined questionnaire- and registry-based study included incident cancer patients diagnosed in the last six months of 2016 where the GP had been involved in the diagnostic process of the patients prior to their diagnosis of cancer (n=3,455). The patient’s travel distance to the first specialised diagnostic facility was calculated by ArcGIS Network Analyst. The diagnostic strategy of the GP and the GP’s satisfaction with the waiting times and the available investigations were assessed from GP questionnaires. Results: When the GP did not suspect cancer or serious illness, an insignificant tendency was seen that longer travel distance to the first specialised diagnostic facility increased the likelihood of the GP using ’wait-and-see’ approach and ’medical treatment’ as diagnostic strategies. The GPs of patients with travel distance longer than 49 kilometres to the first specialised diagnostic facility were more likely to report dissatisfaction with the waiting time for requested diagnostic investigations (PR: 1.98, 95% CI: 1.20-3.28).Conclusion: A insignificant tendency to use ‘wait-and-see’ and ‘medical treatment’ were more likely in GPs of patients with long travel distance to the first diagnostic facility when the GP did not suspect cancer or serious illness. Long distance was associated with higher probability of GP dissatisfaction with the waiting time for diagnostic investigations.


2001 ◽  
Vol 120 (5) ◽  
pp. A370-A370
Author(s):  
C BOBROWSKI ◽  
H GHADIMPOOR ◽  
M STENECK ◽  
X ROGIERS ◽  
C BROELSCH ◽  
...  
Keyword(s):  

Optimization ◽  
1973 ◽  
Vol 4 (6) ◽  
pp. 453-462
Author(s):  
L. Cunningham ◽  
N. Singh

2014 ◽  
Author(s):  
A.M.L. Westin ◽  
C.L. Barksdale ◽  
S.H. Stephan

Nature ◽  
2010 ◽  
Author(s):  
Apoorva Mandavilli
Keyword(s):  

Author(s):  
Shailendra Raghuvanshi ◽  
Priyanka Dubey

Load balancing of non-preemptive independent tasks on virtual machines (VMs) is an important aspect of task scheduling in clouds. Whenever certain VMs are overloaded and remaining VMs are under loaded with tasks for processing, the load has to be balanced to achieve optimal machine utilization. In this paper, we propose an algorithm named honey bee behavior inspired load balancing, which aims to achieve well balanced load across virtual machines for maximizing the throughput. The proposed algorithm also balances the priorities of tasks on the machines in such a way that the amount of waiting time of the tasks in the queue is minimal. We have compared the proposed algorithm with existing load balancing and scheduling algorithms. The experimental results show that the algorithm is effective when compared with existing algorithms. Our approach illustrates that there is a significant improvement in average execution time and reduction in waiting time of tasks on queue using workflowsim simulator in JAVA.


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