Publication result detail

Hierarchical optimisation model for waste management forecasting in EU

SMEJKALOVÁ, V.; ŠOMPLÁK, R.; PLUSKAL, J.; RYBOVÁ, K.

Original Title

Hierarchical optimisation model for waste management forecasting in EU

English Title

Hierarchical optimisation model for waste management forecasting in EU

Type

WoS Article

Original 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.

English 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.

Keywords

Waste forecasting; Circular economy package; Quadratic programming; Trend modelling; Data reconciliation; Confidence intervals

Key words in English

Waste forecasting; Circular economy package; Quadratic programming; Trend modelling; Data reconciliation; Confidence intervals

Authors

SMEJKALOVÁ, V.; ŠOMPLÁK, R.; PLUSKAL, J.; RYBOVÁ, K.

RIV year

2023

Released

01.12.2022

Publisher

SPRINGER

Location

DORDRECHT

ISBN

1389-4420

Periodical

OPTIMIZATION AND ENGINEERING

Volume

23

Number

12

State

United States of America

Pages from

2143

Pages to

2175

Pages count

33

URL

Full text in the Digital Library

BibTex

@article{BUT178742,
  author="Veronika {Smejkalová} and Radovan {Šomplák} and Jaroslav {Pluskal} and Kristýna {Rybová}",
  title="Hierarchical optimisation model for waste management forecasting in EU",
  journal="OPTIMIZATION AND ENGINEERING",
  year="2022",
  volume="23",
  number="12",
  pages="2143--2175",
  doi="10.1007/s11081-022-09735-2",
  issn="1389-4420",
  url="https://link.springer.com/article/10.1007/s11081-022-09735-2"
}

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