CONSIDERATION OF MODELS AND MECHANISMS OF PUBLIC ADMINISTRATION OF PROCUREMENT OF GOODS, WORKS AND SERVICES IN CONSTRUCTION IN UKRAINE

2018 ◽  
Vol 1 (13) ◽  
pp. 131-142
Author(s):  
Tetyana Konstantinovna Mitropan
Keyword(s):  
Public Administration ◽  
Construction Industry ◽  
High Efficiency ◽  
Public Procurement ◽  
Combined Model ◽  
Single Body ◽  
Construction Products ◽  
Model Of Management ◽  
Decentralized Model ◽  
Centralized Model

The article presents the questions of reviewing models and mechanisms of public administration in the procurement of goods, works and services in the field of construction. A comparative analysis of the types of public procurement mechanisms in construction, based on a set of features, has shown the superiority of a centralized type of mechanism that facilitates the introduction of efficient and flexible procurement methods, for example, the conclusion of framework agreements. The author’s vision of the mechanism of state building purchases, in the form of a conceptual model and system differences, is proposed. It is determined that a decentralized model of public procurement management involves the independent implementation by purchasers of procurement, that is, allows each customer to procure goods, works and services in the field of construction. The centralized model of public administration is characterized by the implementation of public procurement in order to provide the general needs of a single body on public procurement, that is, customers commission the implementation of public procurement on their behalf, a centralized body. According to the combined model of management, public procurement in the construction industry takes place under contracts implemented under the centralized model, and the direct ordering and receipt of goods, works, or services takes place according to the rules of a decentralized model. It is noted that according to the system-wide understanding of the mechanism of public administration in the procurement of goods, works and services in the field of construction, it represents a set of specialized management technologies (methods, techniques and tools) that ensure the organization of the process of public procurement of construction products by authorized agents. The direction of this process is determined by the need to implement the principles of vali- dity and innovation, fair choice of the best bidding, prevention of corruption and ensuring the high efficiency of the implementation of public public procurement.

A bargaining game model for efficiency decomposition in the centralized model of two-stage systems

2013 ◽  
Vol 64 (1) ◽  
pp. 103-108 ◽  
Author(s):  
Zhongbao Zhou ◽  
Liang Sun ◽  
Wenyu Yang ◽  
Wenbin Liu ◽  
Chaoqun Ma
Keyword(s):  
Bargaining Game ◽  
Game Model ◽  
Two Stage ◽  
Efficiency Decomposition ◽  
Centralized Model

Quantification of Model-Form Uncertainty in Drift-Diffusion Simulation Using Fractional Derivatives

2015 ◽  
Author(s):  
Yan Wang
Keyword(s):  
Diffusion Processes ◽  
Planck Equation ◽  
Optimization Procedure ◽  
Physical World ◽  
Drift Diffusion ◽  
Long Range Correlations ◽  
Modeling Process ◽  
Model Form ◽  
Generic Description ◽  
Non Gaussian

In modeling and simulation, model-form uncertainty arises from the lack of knowledge and simplification during modeling process and numerical treatment for ease of computation. Traditional uncertainty quantification approaches are based on assumptions of stochasticity in real, reciprocal, or functional spaces to make them computationally tractable. This makes the prediction of important quantities of interest such as rare events difficult. In this paper, a new approach to capture model-form uncertainty is proposed. It is based on fractional calculus, and its flexibility allows us to model a family of non-Gaussian processes, which provides a more generic description of the physical world. A generalized fractional Fokker-Planck equation (fFPE) is proposed to describe the drift-diffusion processes under long-range correlations and memory effects. A new model calibration approach based on the maximum accumulative mutual information is also proposed to reduce model-form uncertainty, where an optimization procedure is taken.

Probability Bounds Analysis Applied to the Sandia Verification and Validation Challenge Problem

2016 ◽  
Vol 1 (1) ◽  
Author(s):  
Aniruddha Choudhary ◽  
Ian T. Voyles ◽  
Christopher J. Roy ◽  
William L. Oberkampf ◽  
Mayuresh Patil
Keyword(s):  
Experimental Data ◽  
Physical Nature ◽  
Distribution Functions ◽  
Verification And Validation ◽  
Cumulative Distribution ◽  
Probability Bounds ◽  
Model Form ◽  
Interval Representation ◽  
Model Predictions ◽  
True System

Our approach to the Sandia Verification and Validation Challenge Problem is to use probability bounds analysis (PBA) based on probabilistic representation for aleatory uncertainties and interval representation for (most) epistemic uncertainties. The nondeterministic model predictions thus take the form of p-boxes, or bounding cumulative distribution functions (CDFs) that contain all possible families of CDFs that could exist within the uncertainty bounds. The scarcity of experimental data provides little support for treatment of all uncertain inputs as purely aleatory uncertainties and also precludes significant calibration of the models. We instead seek to estimate the model form uncertainty at conditions where the experimental data are available, then extrapolate this uncertainty to conditions where no data exist. The modified area validation metric (MAVM) is employed to estimate the model form uncertainty which is important because the model involves significant simplifications (both geometric and physical nature) of the true system. The results of verification and validation processes are treated as additional interval-based uncertainties applied to the nondeterministic model predictions based on which the failure prediction is made. Based on the method employed, we estimate the probability of failure to be as large as 0.0034, concluding that the tanks are unsafe.

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