Publication detail

Forecasting the waste production hierarchical time series with correlation structure

ERYGANOV, I. ROSECKÝ, M. ŠOMPLÁK, R. SMEJKALOVÁ, V.

Original Title

Forecasting the waste production hierarchical time series with correlation structure

Type

journal article in Web of Science

Language

English

Original Abstract

Continuous increase in society's prosperity causes overwhelming growth of the produced municipal solid waste. Circular economy initiatives help to solve this problem by creating closed production cycles, where the produced waste is recycled, or its energy is recovered. An embedment of such principles requires implementation of new waste management strategies. However, these novel strategies must be based on the accurate forecasts of future waste flows. Municipal solid waste production data demonstrate behavior of hierarchical time series. Among all possible approaches to hierarchical times series forecasting, this article is focused on the reconciliation of the base waste generation forecasts. The novel method, that is based on the game-theoretically optimal reconciliation of hierarchical time series, is presented. The modified approach enables to incorporate interdependencies between time series using correlation matrix and to obtain the forecasts corresponding to the unique solution of the optimization problem. The potential of the proposed abstract approach is demonstrated on the waste production data of paper, plastics (both primarily sorted by households), and mixed municipal solid waste from the Czech Republic.

Keywords

Prediction; Waste management; Game theory; Zero-sum game; Nash equilibrium; Optimization

Authors

ERYGANOV, I.; ROSECKÝ, M.; ŠOMPLÁK, R.; SMEJKALOVÁ, V.

Released

2. 7. 2024

Publisher

SPRINGER

Location

DORDRECHT

ISBN

1573-2924

Periodical

OPTIMIZATION AND ENGINEERING

Number

July 2024

State

United States of America

Pages count

23

URL

https://link.springer.com/article/10.1007/s11081-024-09898-0

BibTex

@article{BUT189262,
  author="Ivan {Eryganov} and Martin {Rosecký} and Radovan {Šomplák} and Veronika {Smejkalová}",
  title="Forecasting the waste production hierarchical time series with correlation structure",
  journal="OPTIMIZATION AND ENGINEERING",
  year="2024",
  number="July 2024",
  pages="23",
  doi="10.1007/s11081-024-09898-0",
  issn="1573-2924",
  url="https://link.springer.com/article/10.1007/s11081-024-09898-0"
}