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Askoldas Podviezko   Dr.  University Educator/Researcher 
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Askoldas Podviezko published an article in January 2017.
Top co-authors
Romualdas Ginevicius

94 shared publications

Faculty of Business Managment, Vilnius Gediminas Technical University, Saulėtekio al. 11, LT–10223, Vilnius, Lithuania

Valentinas Podvezko

4 shared publications

Vilnius Gediminas Technical University, Sauletekio al. 11, LT-10223 Vilnius, Lithuania

Publication Record
Distribution of Articles published per year 
(2009 - 2017)
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Article 4 Reads 7 Citations Assessment of efficiency of assignment of vehicles to tasks in supply chains: a case study of a municipal company Ilona Jacyna-Gołda, Mariusz Izdebski, Askoldas Podviezko Published: 17 January 2017
Transport, doi: 10.3846/16484142.2016.1275040
DOI See at publisher website ABS Show/hide abstract
The main purpose of the paper is to present criteria of efficiency of assignment of vehicles to tasks at municipal companies, which collect garbage from city inhabitants. Three types of criteria are introduced in the paper: garbage collection time, length of route allocation, and utilization of resources. A two-stage method of optimization of task-routes is proposed. It generates tasks at the first stage and assigns vehicles to the tasks at the second stage. At municipal companies that are responsible for garbage, collection tasks are not pre-defined, and consequently tasks must be designated before the workday. The proposed method is based on genetic algorithm, which is used for the purpose of optimization of the assignment problem. The obtained by the algorithm optimal assignment is compared with assignments obtained in the random way. Criteria of evaluation of efficiency of the obtained route of different mutually conflicting dimensions were introduced, such as is task realization time, distances travelled on particular routes, and number of vehicles involved in garbage collection. Efficiency of the obtained assignment appeared to be sufficiently good.
Article 0 Reads 4 Citations COMPARATIVE ANALYSIS OF TAX CAPACITY IN REGIONS OF RUSSIA Lyudmila Parfenova, Andrey Pugachev, Askoldas Podviezko Published: 23 November 2016
Technological and Economic Development of Economy, doi: 10.3846/20294913.2016.1216019
DOI See at publisher website
Article 0 Reads 1 Citation Processing Digital Images for Crack Localization in Reinforced Concrete Members Arvydas Rimkus, Askoldas Podviezko, Viktor Gribniak Published: 01 January 2015
Procedia Engineering, doi: 10.1016/j.proeng.2015.10.031
DOI See at publisher website ABS Show/hide abstract
Cracks are among the most frequent types of damage occurring in concrete structures. The structural inspection often requires application of non-destructive techniques for localization of damages, and for validation of the structural integrity. Traditionally, cracks are localized and measured using crack width templates or microscopes, and consequently the crack pattern is transferred to a drawing sheet manually. These operations imply a high level of imperfection, subjectivity of judgment, furthermore they are time-consuming. In the engineering practice, digital image analysis systems can be implemented for reliable detection of concrete surface cracking. In this paper, such procedure is proposed. Images obtained by Digital Image Correlation technique are used for the crack localization. The image processing is performed in two steps. First, the image is modified to achieve strictly horizontal position for the purpose of removing effect of perspective and shape deformation. Ambient noise is also reduced. Subsequently, the vertical shape of cracks is used in order to localize their position. The Agglomerative Hierarchical Clustering Technique is used at the second analysis step for identifying the “cracking pixels” (projections) that closely resemble one another. The proposed algorithm can be applied to datasets of the images generated at different loading levels for the purpose of producing a diagram that represents evolution of the crack distances with increasing load. It is illustrated using the experimental data obtained by the authors.
Article 0 Reads 3 Citations Influence of Data Transformation on Multicriteria Evaluation Result Askoldas Podviezko, Valentinas Podvezko Published: 01 January 2015
Procedia Engineering, doi: 10.1016/j.proeng.2015.10.019
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The main idea of quantitative multiple criteria decision-making methods (MCDM) is comprising values of a chosen set of criteria into a single cumulative criterion of evaluation. Units of measurement can be different: per cent, ranks, grades, money units, physical units, etc. Consequently, their incorporation into a single evaluation criterion is possible if values of criteria are independent of units of measurement. Such dimensionless values are obtained by normalizing the values. Criteria can be both minimizing and maximizing. Some MCDA methods imply transformation of minimizing criteria into maximizing ones. Moreover, values of criteria can me negative (profit, growth rate, etc.), but some MCDA methods can use only positive criteria. Therefore, majority of MCDA methods use both normalization and transformation of criteria with negative values. There are different formulae available. Even in the same method different transformation and normalization formulae can be used. Nevertheless, using different transformation and normalization formulae can lead to differences in results of evaluation. In this paper it is shown that different types of transformation and normalization of data applied to popular MCDA methods, such as SAW or TOPSIS may produce considerable differences in evaluation. Consequently, attention has to be paid to making a choice of the type of normalization, which reveals preferences of decision-maker. Dependence of evaluation results on the chosen type of transformation or normalization is demonstrated. A case-study is provided.
CONFERENCE-ARTICLE 7 Reads 0 Citations Aspects of Absolute Evaluation of Financial Stability State of Commercial Banks Askoldas Podviezko Published: 06 November 2014
The 4th World Sustainability Forum, doi: 10.3390/wsf-4-c003
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Concern on financial stability of commercial banks is an ongoing issue, requiring permanent reviewing of regulatory frameworks and developing new approaches. Currently static regulatory methodologies are prevailing, which set pre-defined minimal requirements on limited financial parameters, such as capital or liquidity. The number of such indicative parameters cannot reflect overall performance of a bank because the set of monitored parameters is insufficient and because each financial stability parameter is monitored separately. Moreover, such parameters are static. Dynamic setting of values of minimal or desired parameters of financial performance of commercial banks should be more effective, in case we decide that we ought to vary requirements on banks over changing macroeconomic environment. Evaluation based on multiple criteria decision-aid (MCDA) methods comprises simultaneously several multidimensional criteria and provides results of evaluation in a clear form for both financier and everyman-depositor. Such an evaluation of financial stability state of the banks is providing more holistic approach. Moreover, it can considerably reduce information asymmetry between depositors and commercial banks, which may have positive effect on financial stability.Existing methodology of absolute MCDA evaluation provides an efficient tool of altering benchmark banks, hypothetical best and worst banks, comparing to which the evaluation is carried out, thus allowing to alter requirements for banks upon shifts of financial environment.
CONFERENCE-ARTICLE 9 Reads 0 Citations Evaluation of Level of Heterogeneity of Socio-Economic Development of a Country Valentinas Podvezko, Askoldas Podviezko Published: 31 October 2014
The 4th World Sustainability Forum, doi: 10.3390/wsf-4-d006
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Heterogeneity of levels of socio-economic development of countries or country's different regions is undesirable. For the sake of sustainable development of a country or group of countries it is important to elicit relative levels of development of country's regions or different countries, and to find the weakest indicators of their development. Socio-economic development of a country or group of countries depends on a variety of factors. Statistics Department of Lithuania provides annual data describing the state of all 10 counties of Lithuania by 162 criteria. 60 criteria describe economic development, 94 describe social development, and finally, ecological state is described by 8 criteria. Prevailing in literature comparative analysis by separately selected criteria, as important as GDP per capita, often does not provide an extensive picture of quality of life of country's citizens. A comprehensive approach is required for evaluating of level of development of countries or country's regions. A suitable tool, which promptly provides quantitative evaluation of level of development of country's regions, provides results in a clear comprehensible form, and comprises the whole variety of important multi-dimensional criteria is multiple criteria decision-making (MCDM) methods. Experienced experts evaluate weights of importance of criteria used in the research, keeping in mind the major aim of the evaluation. Weights and values of criteria are comprised into a single cumulative criterion of a MCDA method. Comparative analysis of evaluation over a lengthy period of time allows to analyse dynamics of development of the regions, and to elicit levels of dependence of different criteria on the general level of development and welfare. MCDM methods allow revealing weaknesses of development of every region and provide a strong support for decision-makers and politicians for their effective actions intended for sustainable development of regions.