Resource Allocation Strategies for a non-Continuous Sliding Window Traffic Model in WDM Networks

2009 ◽  
Author(s):  
Ying Chen ◽  
Arunita Jaekel ◽  
Ataul Bari
Keyword(s):  
Resource Allocation ◽  
Sliding Window ◽  
Wdm Networks ◽  
Traffic Model ◽  
Allocation Strategies

scholarly journals Balancing scarce hospital resources during the COVID-19 pandemic using discrete-event simulation

2021 ◽  
Author(s):  
G.J. Melman ◽  
A.K. Parlikad ◽  
E.A.B. Cameron
Keyword(s):  
Resource Allocation ◽  
Discrete Event Simulation ◽  
Elective Surgery ◽  
Discrete Event ◽  
Specific Patient ◽  
Event Simulation ◽  
The Impact ◽  
Allocation Decisions ◽  
Allocation Strategies ◽  
Resource Allocation Decisions

AbstractCOVID-19 has disrupted healthcare operations and resulted in large-scale cancellations of elective surgery. Hospitals throughout the world made life-altering resource allocation decisions and prioritised the care of COVID-19 patients. Without effective models to evaluate resource allocation strategies encompassing COVID-19 and non-COVID-19 care, hospitals face the risk of making sub-optimal local resource allocation decisions. A discrete-event-simulation model is proposed in this paper to describe COVID-19, elective surgery, and emergency surgery patient flows. COVID-19-specific patient flows and a surgical patient flow network were constructed based on data of 475 COVID-19 patients and 28,831 non-COVID-19 patients in Addenbrooke’s hospital in the UK. The model enabled the evaluation of three resource allocation strategies, for two COVID-19 wave scenarios: proactive cancellation of elective surgery, reactive cancellation of elective surgery, and ring-fencing operating theatre capacity. The results suggest that a ring-fencing strategy outperforms the other strategies, regardless of the COVID-19 scenario, in terms of total direct deaths and the number of surgeries performed. However, this does come at the cost of 50% more critical care rejections. In terms of aggregate hospital performance, a reactive cancellation strategy prioritising COVID-19 is no longer favourable if more than 7.3% of elective surgeries can be considered life-saving. Additionally, the model demonstrates the impact of timely hospital preparation and staff availability, on the ability to treat patients during a pandemic. The model can aid hospitals worldwide during pandemics and disasters, to evaluate their resource allocation strategies and identify the effect of redefining the prioritisation of patients.

LEARNING OF RESOURCE ALLOCATION STRATEGIES FOR GAME PLAYING

1996 ◽  
Vol 12 (1) ◽  
pp. 88-105 ◽  
Author(s):  
Shaul Markovitch ◽  
Yaron Sella
Keyword(s):  
Resource Allocation ◽  
Game Playing ◽  
Allocation Strategies

Resource-Allocation Strategies: A Verbal Protocol Analysis

1998 ◽  
Vol 76 (1) ◽  
pp. 70-88 ◽  
Author(s):  
Christopher T Ball ◽  
Harvey J Langholtz ◽  
Jacqueline Auble ◽  
Barron Sopchak
Keyword(s):  
Resource Allocation ◽  
Protocol Analysis ◽  
Verbal Protocol ◽  
Verbal Protocol Analysis ◽  
Allocation Strategies

scholarly journals Sex allocation conflict and sexual selection throughout the lifespan of eusocial colonies

2018 ◽  
Author(s):  
Piret Avila ◽  
Lutz Fromhage ◽  
Laurent Lehmann
Keyword(s):  
Resource Allocation ◽  
Sexual Selection ◽  
Evolutionary Biology ◽  
Sex Allocation ◽  
Colony Growth ◽  
Eusocial Insects ◽  
Dynamic Resource ◽  
Colony Ontogeny ◽  
Allocation Decisions ◽  
Allocation Strategies

AbstractModels of sex allocation conflict are central to evolutionary biology but have mostly assumed static decisions, where resource allocation strategies are constant over colony lifespan. Here, we develop a model to study how the evolution of dynamic resource allocation strategies is affected by the queen-worker conflict in annual eusocial insects. We demonstrate that the time of dispersal of sexuals affects the sex allocation ratio through sexual selection on males. Furthermore, our model provides three predictions that depart from established results of classic static allocation models. First, we find that the queen wins the sex allocation conflict, while the workers determine the maximum colony size and colony productivity. Second, male-biased sex allocation and protandry evolve if sexuals disperse directly after eclosion. Third, when workers are more related to new queens, then the proportional investment into queens is expected to be lower, which results from the interacting effect of sexual selection (selecting for protandry) and sex allocation conflict (selecting for earlier switch to producing sexuals). Overall, we find that colony ontogeny crucially affects the outcome of sex-allocation conflict because of the evolution of distinct colony growth phases, which decouples how queens and workers affect allocation decisions and can result in asymmetric control.

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