scholarly journals Variables Reduction in Sequential Resource Allocation Problems

2020 ◽  
Vol 3 (2) ◽  
pp. 21
Author(s):  
Juri Hinz ◽  
Tiziano Vargiolu
Keyword(s):  
Decision Problem ◽  
Pension Fund ◽  
Original Formulation ◽  
Problem Class ◽  
Decision Variables ◽  
Optimal Resource ◽  
Sequential Resource Allocation ◽  
Optimal Resource Management ◽  
And Storage ◽  
Natural Reserves

This paper presents a general framework to address diverse notoriously difficult problems arising in the area of optimal resource management, exploitation of natural reserves, pension fund valuation, environmental protection, and storage operation. Using some common abstract features of this problem class, we present a technique which provides a significant reduction of decision variables. As an application, we discuss a battery storage control to show how a decision problem, which is practically unsolvable in the original formulation, can be treated by our method.

Optimal Resource Usage in Multi-Cloud Computing Environment

2013 ◽  
Vol 3 (1) ◽  
pp. 44-57 ◽  
Author(s):  
Veena Goswami ◽  
Choudhury Nishkanta Sahoo
Keyword(s):  
Cloud Computing ◽  
Service Providers ◽  
Queueing Network ◽  
Computing Environment ◽  
New Paradigm ◽  
Cloud Computing Environment ◽  
Optimal Resource ◽  
Optimal Resource Management ◽  
And Performance ◽  
Multi Cloud

Cloud computing has emerged as a new paradigm for accessing distributed computing resources such as infrastructure, hardware platform, and software applications on-demand over the internet as services. This paper presents an optimal resource management framework for multi-cloud computing environment. The authors model the behavior and performance of applications to integrate different service-providers for end-to-end-requirements. Each service model caters to specific type of requirements and there are already number of players with own customized products/services offered. Intercloud Federation and Service delegation models are part of Multi-Cloud environment where the broader target is to achieve infinite pool of resources. They propose an analytical queueing network model to improve the efficiency of the system. Numerical results indicate that the proposed provisioning technique detects changes in arrival pattern, resource demands that occur over time and allocates multiple virtualized IT resources accordingly to achieve application Quality of Service targets.

Solving Decision Problems with Mathematical Expectation

2011 ◽  
Vol 128-129 ◽  
pp. 293-296
Author(s):  
Mei Zhang ◽  
Jing Hua Wen
Keyword(s):  
Mathematical Expectation ◽  
Decision Problem ◽  
Random Variables ◽  
Decision Problems ◽  
Employment Decision ◽  
Decision Variables ◽  
Project Contract

Mathematical expectation is one of the important digital characters of the random variables. Many decision variables in decision problem are random variables; it is difficult to define their concrete distribution, while we can use their mathematical expectation to resolve decision questions. The applications of mathematical expectation in decision question were analyzed by example from two aspects of project contract decision and obtain employment decision.

Validation en temps réel des données hydrométriques

2003 ◽  
Vol 30 (1) ◽  
pp. 212-225
Author(s):  
Berrada Faouzi ◽  
Khalili Malika ◽  
Bennis Saad
Keyword(s):  
Kalman Filter ◽  
Real Time ◽  
Multiple Regression Equation ◽  
Variation Trend ◽  
Regressive Model ◽  
Analytical Redundancy ◽  
Optimal Resource ◽  
Auto Regressive ◽  
Optimal Resource Management ◽  
Auto Regressive Model

The managers of hydrological systems take real-time level and discharge measurements on several reservoirs and river reaches. The measurements are frequently tainted with errors that are reflected by uncertainties in decision making and by non-optimal resource management. This article aims at developing a methodology for the validation of levels in real-time. The proposed approach is based on material and analytical redundancy, and uses two models. The first one is spatial and enables linking of the measurements carried out at different stations with the help of a multiple regression equation. The second one is temporal, which enables the determination of variation trend at the different stations with the help of an auto-regressive model. These two models are incorporated into a diagnosis system for breakdowns based on a logic vote principle. Among the values that are measured and estimated by the linear regression model, the one which is the most consistent with the variation trend indicated by the auto-regressive model is selected. The Kalman filter is used to filter the measurements and identify the parameters of the models used in real-time. The proposed methodology turned out to be conclusive when applied to both measured data and synthetic hydrographs.Key words: validation, real-time, material redundancy, analytical redundancy, regressive, auto-regressive, Kalman filter.

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