Optimal allocation of resources in distributed information networks

1976 ◽  
Vol 1 (1) ◽  
pp. 66-78 ◽  
Author(s):  
Samy Mahmoud ◽  
J. S. Riordon
Biometrika ◽  
2021 ◽  
Author(s):  
Lorenzo Masoero ◽  
Federico Camerlenghi ◽  
Stefano Favaro ◽  
Tamara Broderick

Abstract While the cost of sequencing genomes has decreased dramatically in recent years, this expense often remains non-trivial. Under a fixed budget, scientists face a natural trade-off between quantity and quality: spending resources to sequence a greater number of genomes or spending resources to sequence genomes with increased accuracy. Our goal is to find the optimal allocation of resources between quantity and quality. Optimizing resource allocation promises to reveal as many new variations in the genome as possible. In this paper, we introduce a Bayesian nonparametric methodology to predict the number of new variants in a follow-up study based on a pilot study. When experimental conditions are kept constant between the pilot and follow-up, we find that our prediction is competitive with the best existing methods. Unlike current methods, though, our new method allows practitioners to change experimental conditions between the pilot and the follow-up. We demonstrate how this distinction allows our method to be used for more realistic predictions and for optimal allocation of a fixed budget between quality and quantity.


1990 ◽  
Vol 17 (3) ◽  
pp. 174-176
Author(s):  
Lis Andersen ◽  
Dorthe Arenholt-Bindslev

Quantification of toxicity-induced cytomorphological effects in an epithelial cell culture system is described. Estimates of volume density and star volume of mitochondria and lysosomes are given. Mean volumes (n = 5) and coefficients of variation of these parameters were equal in experimental (TPA-treatment) and control cultures. An optimal allocation of resources for estimating cytomorphometric parameters would be to increase the number of culture flasks.


2018 ◽  
Vol 17 (1) ◽  
pp. 49-58 ◽  
Author(s):  
Justyna Góral ◽  
Włodzimierz Rembisz

The optimal allocation of resources in various sectors results in the sustainable development of the whole economy (the theory of optimum allocation of resources by Kantonowicz and Koopmans). According to Tinbergen’s studies, the excessive labour force in one of them gives rise to all types of social and economic problems. The objective of theoretical considerations and empirical studies of this publication is to analyse the ratio of the remuneration for labour to its productivity in various economy sectors with particular attention paid to the agricultural sector. The authors also refer to the theory by Lewis and Schultz, who had analysed the problems of agriculture in developing countries, as well as to the Solow economic growth model with the Cobb–Douglas production function. In the light of the empirical data presented in the paper, we can conclude that in section A of Statistical Classification of Economic Activities this ratio is seriously disturbed and distorted. The remuneration is overvalued in relation to the labour productivity. Such a ratio is not a positive testimony to the reasonableness of management in the sense of agricultural producers’ equilibria.


1992 ◽  
Vol 24 (4) ◽  
pp. 894-914 ◽  
Author(s):  
Moshe Shaked ◽  
J. George Shanthikumar

In this paper we consider parallel and series systems, the components of which can be ‘improved'. The ‘improvement' consists of supplying the components with cold or hot standby spares or by allotting to them fixed budgets for minimal repairs. A fixed total resource of spares or minimal repairs is available. We find the optimal allocation of the resource items in several commonly encountered settings.


Author(s):  
Nandan Sudarsanam ◽  
Ramya Chandran ◽  
Daniel D. Frey

Abstract This research studies the use of predetermined experimental plans in a live setting with a finite implementation horizon. In this context, we seek to determine the optimal experimental budget in different environments using a Bayesian framework. We derive theoretical results on the optimal allocation of resources to treatments with the objective of minimizing cumulative regret, a metric commonly used in online statistical learning. Our base case studies a setting with two treatments assuming Gaussian priors for the treatment means and noise distributions. We extend our study through analytical and semi-analytical techniques which explore worst-case bounds and the generalization to k treatments. We determine theoretical limits for the experimental budget across all possible scenarios. The optimal level of experimentation that is recommended by this study varies extensively and depends on the experimental environment as well as the number of available units. This highlights the importance of such an approach which incorporates these factors to determine the budget.


2020 ◽  
pp. 118-129
Author(s):  
Greg Fisher ◽  
John E. Wisneski ◽  
Rene M. Bakker

Value chain analysis (VCA) aids the strategist in understanding a firm’s potential sources of competitive advantage by decomposing the firm’s business processes into strategically important activities. Viewing the firm as an aggregate of interlinked value-adding activities and placing them in the context of a broader value chain helps to understand each activity’s impact on both cost and revenue potential. As such, VCA can be used to help the firm achieve an optimal allocation of resources. This chapter discusses the underlying theory, core idea, depiction, process, insight or value created, and risks and limitations of VCA. The chapter also continues the illustration of Netflix and applies the steps of value chain analysis to this case.


2017 ◽  
Vol 32 (S1) ◽  
pp. S229
Author(s):  
Irene Christodoulou ◽  
George M. Milis ◽  
Panayiotis Kolios ◽  
Christos Panayiotou ◽  
Marios Polycarpou ◽  
...  

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