Optimal Allocation of Resources for Defense of Simple Series and Parallel Systems from Determined Adversaries

2003 ◽  
Author(s):  
Vicki M. Bier ◽  
Vinod Abhichandani
Keyword(s):  
Optimal Allocation ◽  
Parallel Systems ◽  
Allocation Of Resources

scholarly journals More for less: predicting and maximizing genomic variant discovery via Bayesian nonparametrics

Biometrika ◽  
2021 ◽  
Author(s):  
Lorenzo Masoero ◽  
Federico Camerlenghi ◽  
Stefano Favaro ◽  
Tamara Broderick
Keyword(s):  
Optimal Allocation ◽  
Bayesian Nonparametrics ◽  
Allocation Of Resources ◽  
Experimental Conditions ◽  
Follow Up Study ◽  
Variant Discovery ◽  
Fixed Budget ◽  
The Cost ◽  
Genomic Variant

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.

Morphometric Registration of Cytotoxic Changes of Epithelial Cells In Vitro: A Methodological Study

1990 ◽  
Vol 17 (3) ◽  
pp. 174-176
Author(s):  
Lis Andersen ◽  
Dorthe Arenholt-Bindslev
Keyword(s):  
Culture System ◽  
Optimal Allocation ◽  
Volume Density ◽  
Cell Culture System ◽  
Allocation Of Resources ◽  
Methodological Study ◽  
Epithelial Cell Culture ◽  
Coefficients Of Variation ◽  
And Control

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.

Optimal allocation of a coherent system with statistical dependent subsystems

2021 ◽  
pp. 1-20
Author(s):  
Bin Lu ◽  
Jiandong Zhang ◽  
Rongfang Yan
Keyword(s):  
Hazard Rate ◽  
Optimal Allocation ◽  
Stochastic Order ◽  
Sufficient Conditions ◽  
Parallel Systems ◽  
Coherent System ◽  
Allocation Policy ◽  
Usual Stochastic Order ◽  
Series Systems ◽  
Parallel Series

Abstract This paper studies the optimal allocation policy of a coherent system with independent heterogeneous components and dependent subsystems, the systems are assumed to consist of two groups of components whose lifetimes follow proportional hazard (PH) or proportional reversed hazard (PRH) models. We investigate the optimal allocation strategy by finding out the number $k$ of components coming from Group A in the up-series system. First, some sufficient conditions are provided in the sense of the usual stochastic order to compare the lifetimes of two-parallel–series systems with dependent subsystems, and we obtain the hazard rate and reversed hazard rate orders when two subsystems have independent lifetimes. Second, similar results are also obtained for two-series–parallel systems under certain conditions. Finally, we generalize the corresponding results to parallel–series and series–parallel systems with multiple subsystems in the viewpoint of the minimal path and the minimal cut sets, respectively. Some numerical examples are presented to illustrate the theoretical findings.

Optimal Allocation of Components in k-out-of-R Parallel Modules Systems

1994 ◽  
Vol 8 (3) ◽  
pp. 435-441 ◽  
Author(s):  
Fan Chin Meng
Keyword(s):  
System Reliability ◽  
Optimal Allocation ◽  
Parallel Systems ◽  
Coherent Systems ◽  
Special Case

In this note using the notion of node criticality in Boland, Proschan, and Tong [2] and modular decompositions of coherent systems, we obtain algorithms and guidelines for allocating components in a k-out-of-R parallel modules system to maximize the system reliability. An illustrative example is given to compare a special case of our results with the previous result for series-parallel systems due to El-Neweihi, Proschan, and Sethuraman [5].

scholarly journals REMUNERATIONS AND LABOUR PRODUCTIVITY IN AGRICULTURE AGAINST A BACKGROUND OF OTHER ECONOMY SECTORS

2018 ◽  
Vol 17 (1) ◽  
pp. 49-58 ◽  
Author(s):  
Justyna Góral ◽  
Włodzimierz Rembisz
Keyword(s):  
Agricultural Sector ◽  
Optimal Allocation ◽  
Labour Force ◽  
Empirical Studies ◽  
Labour Productivity ◽  
Allocation Of Resources ◽  
Economic Activities ◽  
Agricultural Producers ◽  
The Sustainable Development ◽  
Economic Growth Model

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.

Optimal allocation of resources to nodes of parallel and series systems

1992 ◽  
Vol 24 (4) ◽  
pp. 894-914 ◽  
Author(s):  
Moshe Shaked ◽  
J. George Shanthikumar
Keyword(s):  
Optimal Allocation ◽  
Allocation Of Resources ◽  
Series Systems ◽  
Total Resource

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.

scholarly journals Conducting Non-Adaptive Experiments in a Live Setting: A Bayesian Approach to Determining Optimal Sample Size

2019 ◽  
Author(s):  
Nandan Sudarsanam ◽  
Ramya Chandran ◽  
Daniel D. Frey
Keyword(s):  
Statistical Learning ◽  
Optimal Allocation ◽  
Analytical Techniques ◽  
Optimal Level ◽  
Base Case ◽  
Allocation Of Resources ◽  
Worst Case ◽  
Optimal Sample Size ◽  
Optimal Sample ◽  
Theoretical Results

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.

Value Chain Analysis

2020 ◽  
pp. 118-129
Author(s):  
Greg Fisher ◽  
John E. Wisneski ◽  
Rene M. Bakker
Keyword(s):  
Competitive Advantage ◽  
Value Chain ◽  
Business Processes ◽  
Optimal Allocation ◽  
P Value ◽  
Allocation Of Resources ◽  
Value Chain Analysis ◽  
Chain Analysis ◽  
Potential Sources ◽  
Core Idea

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.

scholarly journals Enhanced Situational Awareness through a Decision Support Service for Optimal Allocation of Resources and Response Capacity

2017 ◽  
Vol 32 (S1) ◽  
pp. S229
Author(s):  
Irene Christodoulou ◽  
George M. Milis ◽  
Panayiotis Kolios ◽  
Christos Panayiotou ◽  
Marios Polycarpou ◽  
...  
Keyword(s):  
Decision Support ◽  
Optimal Allocation ◽  
Situational Awareness ◽  
Support Service ◽  
Allocation Of Resources ◽  
Response Capacity
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