Verification of Information in Large Databases by Mathematical Programming in Waste Management
AbstractThe obligation to register production and waste management leads to a formation of a large-scale database. The reporting obligation concerns immediately a large number of subject that may cause discrepancies in reported data. The paper presents an approach for error detection in large data files. Errors are reflected as inconsistency in total production and processing or in transportation between two nodes. In this case, the area (node), that has sent the waste, registers a different quantity than the node that has received the waste. The database of waste management is an essential source of information for many calculations and analysis, which further open up the scope for the realisation of projects, so it is important to have accurate data. This paper presents an approach for identifying errors in the database using mathematical programming techniques. This issue was solved as a task of network flow with an emphasis on the force of mass balance in nodes. The objective is to make the amount of produced and delivered waste to each node equal to the amount that was there processed or removed. This is required with the minimum modification of the input data. Weights are introduced to distinguish high and low-quality data by assigning bigger values to arcs where sent amount correspond with quantity received. In this case, there is no reason to consider the data as erroneous. This tool has been tested through a case study on the database of waste management in the Czech Republic. The considered network consists of 206 nodes representing municipalities, which corresponds to 42,230 edges (possible flows). The output from the calculation is a large amount of data, which are in terms of approximation to initial values interpreted as maps. However, the tool could be used for other areas of records and databases, where there is a transfer of any material flow. In the further research, the model can be supplemented by specific constraints arising from additional information for the specific application. In this case, decision-making about network flow would be done with taking into account the shortest distance between producers and treatment facilities.
How to Cite
Šomplák R., Nevrlý V., Smejkalová V., Pavlas M., Kůdela J., 2017, Verification of Information in Large Databases by Mathematical Programming in Waste Management , Chemical Engineering Transactions, 61, 985-990.