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Methods of economic-mathematic programming in managerial decision making
2015
Smoliarchuk, M., Lviv National Agrarian Univ. (Ukraine) | Soltys, O., Lviv National Agrarian Univ. (Ukraine) | Kulbaka, V., Lviv National Agrarian Univ. (Ukraine)
The article reveals difficulties to make managerial decisions as to optimization of recreational objects’ location considering economic and technological parameters of an impact with application of fuzzy modelling. The authors propose methods of evaluation of alternative variants of managerial decision making applying programs of Mathcad with the further prospect of choosing alternatives.
Afficher plus [+] Moins [-]Application of mathematical-cartographic modelling in optimising the structure of the regional landfill of solid non-hazardous waste of the Lutsk management cluster [Ukraine]
2021
Korol, P., Lesya Ukrainka Volyn National Univ., Lutsk (Ukraine) | Petrovych, O., National Univ. of Life and Environmental Sciences of Ukraine, Kiev (Ukraine) | Pavlyshyn, V., Rivne Research and Design Inst. of Land Management, SE, Lutsk (Ukraine). Volyn Branch
Ukraine is one of the countries where the problem of waste management is particularly acute and deteriorating every year. The Regional Waste Management Plan in Volyn region by 2030 envisages a reduction in the total amount of landfilled waste from 97.68% to 30%, and the number of sites for their disposal – up to 4–8 regional landfills per region. Ecological-economic mechanism of solid non-hazardous waste (SNHW) management is based on a harmonious combination of environmental constraints with the economic attractiveness of regional landfills and involves working with geographically defined objects based on the use of methods of processing geospatial information, one of which is mathematical-cartographic modelling. Thus, the main purpose of this work is to substantiate the possibilities of applying the method of mathematical-cartographic modelling in the design of the system of regional landfills of SNHW in the Volyn region. In order to address the issue of placement of SNHW management facilities, the territory of the region is divided into four management clusters. The division of the territory took into account the composition, properties, methods of solid waste collection, logistics, load on waste processing complexes, volumes of waste generated, spatial planning, etc. Three probable options for the location of regional landfills have been developed for the Lutsk SNHW cluster. The results of the study can be used in the development and adjustment of regional plans, waste management programs, as well as in the work of the executive bodies of the united territorial communities.
Afficher plus [+] Moins [-]Possibilities use to selected methods of spatial data mining in demographic data analytics
2018
Kurowska, K., University of Warmia and Mazury in Olsztyn (Poland). Faculty of Geodesy, Geospatial and Civil Engineering | Kietlinska, E., University of Warmia and Mazury in Olsztyn (Poland). Faculty of Geodesy, Geospatial and Civil Engineering | Kryszk, H., University of Warmia and Mazury in Olsztyn (Poland). Faculty of Geodesy, Geospatial and Civil Engineering
The main purpose of data mining in private and public sector institutions is to process and analyse data with the aim of generating reliable information for decision-making. Decision-making performance is determined by the availability of the relevant data and the user’s ability to adapt that data for analytical purposes. The popularity of spatial statistical tools is on the rise owing to the complexity of the analysed factors, their variation over time and their correlations with the spatial structure. Popular models should be applied in demographic analyses for the needs of the spatial planning process. The availability of high-resolution data and accurate analytical tools enhances the value of spatial analyses, and the described models can be universally applied to support the decision-making process. The aim of this study was to present the applicability of selected spatial statistical models for analysing demographic data in the planning process and to identify the main advantages of these models.
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