| Title |
Hierarchical optimisation model for waste management forecasting in EU |
| ID_Doc |
6169 |
| Authors |
Smejkalova, V; Somplák, R; Pluskal, J; Rybová, K |
| Title |
Hierarchical optimisation model for waste management forecasting in EU |
| Year |
2022 |
| Published |
Optimization And Engineering, 23, 4 |
| DOI |
10.1007/s11081-022-09735-2 |
| Abstract |
The level of waste management varies significantly from one EU state to another and therefore they have different starting position regarding reaching defined EU targets. The forecast of waste production and treatment is essential information for the expected future EU targets fulfilment. If waste treatment does not meet the targets under the current conditions, it is necessary to change waste management strategies. This contribution presents a universal approach for forecasting waste production and treatment using optimisation models. The approach is based on the trend analysis with the subsequent data reconciliation (quadratic programming). The presented methodology also provides recommendations to include the quality of trend estimate and significance of territory in form of weights in objective function. The developed approach also allows to put into context different methods of waste handling and production. The variability of forecast is described by prediction and confidence intervals. Within the EU forecast, the expected demographic development is taken into account. The results show that most states will not meet EU targets with current trend of waste management in time. Presented methodology is developed at a general level and it is a suitable basis for strategic planning at the national and transnational level. |
| Author Keywords |
Waste forecasting; Circular economy package; Quadratic programming; Trend modelling; Data reconciliation; Confidence intervals |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:000815437600001 |
| WoS Category |
Engineering, Multidisciplinary; Operations Research & Management Science; Mathematics, Interdisciplinary Applications |
| Research Area |
Engineering; Operations Research & Management Science; Mathematics |
| PDF |
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