The data regarding the current potential of unrecyclable waste and its spatial distribution play an essential role in the planning process. As per the circular economy strategies, especially the bulky waste streams suitable for energy recovery are to be identified. The public databases, however, collect data from a variety of sources (production and handling reports), which implies the presence of errors. This paper therefore proposes a multi-objective approach to identification and elimination of such errors to improve the accuracy of the assessment of potential energy recovery. The discussed model tracks the flow of waste from producers to processing nodes and minimises the deviation from the original data. Economic aspects are considered as well by preferring the shortest transport distance. The combination of data reconciliation and network flow enhances performance, as objective functions are solved separately, and only then the normalised individual optima are used in the multi-objective function. The model was tested using a Czech Republic regional-level dataset from 2015. A new perspective on the current state of waste management was provided, and valuable information for future planning was revealed, which can be useful for modelling of flows of other commodities. (C) 2019 Elsevier Ltd. All rights reserved.