Hierarchical optimisation model for waste management forecasting in EU

Šmejkalová, Veronika; Šomplák, Radovan; Pluskal, Jaroslav; Rybová, Kristýna

doi:10.1007/s11081-022-09735-2

Cited by 9 publications

(1 citation statement)

References 32 publications

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“…If waste treatment plans are insufficient for meeting the targets, then is necessary to change waste management strategies. The paper by Smejkalová et al (2022) outlines an optimization-based approach for forecasting total waste amounts and the amounts of waste fractions requiring treatment in an area (e.g., country) divided into territories. The forecasts rely on trend analysis followed by data reconciliation employing quadratic programming.…”

Section: Overview Of the Special Issue Articlesmentioning

confidence: 99%

Introductory remarks on the special issue of Optimization and Engineering dedicated to SDEWES 2021 conference

et al. 2022

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The background of this Special Issue (SI) of the Optimization and Engineering (OPTE) journal is the 2021 Sustainable Development of Energy, Water and Environment Systems (SDEWES) Conference. This broad field was discussed by the participants of the 16th SDEWES Conference held in Dubrovnik, Croatia. This SI aims to bring together articles that discuss recent advances in optimization methods and algorithms that integrate various life-supporting systems. A decision-making problem often appears as a parameter estimation problem; it can be formulated as an optimization model and solved using different optimization algorithms and techniques. All papers included in this OPTE journal SI consider aspects of numerical analysis, mathematical modelling, and computational methods involved in investigating, planning and implementing sustainable development. In this context, the guest editors have confidence that the selected papers and addressed issues will substantially contribute to the increase of the knowledge body published in the OPTE journal, and the SI will be a powerful platform for researchers to discuss, share, and disseminate new ideas.

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Section: Overview Of the Special Issue Articlesmentioning

confidence: 99%

Introductory remarks on the special issue of Optimization and Engineering dedicated to SDEWES 2021 conference

et al. 2022

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Modelling the impact of legislative interventions on future waste production within territorial division

Smejkalová,

Šomplák,

Pluskal

2024

Clean Techn Environ Policy

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Network flow problem heuristic reduction using machine learning

Rosecký,

Pluskal,

Šomplák

2023

Optim Eng

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Most of the supporting tools developed for logistic optimization and processing infrastructure planning are based on the network flow problem. The real-world application of these instruments can provide great insight and help to ensure long-term sustainability. The main limitation of these tools lies in great computing demand when there is the necessity of solving large-scale tasks in great detail. It means that the ability to find the optimal solution for real-world problems is limited. Thus, the detail of infrastructure is often reduced by data aggregation or heuristic approaches are used to find a suboptimal solution. This paper proposes a machine learning classification model to reduce the number of variables for an exact solution algorithm. First, the design of experiments is used to create a set of smaller problems that are possible to solve exactly. Artificial data are used at this stage, while domain knowledge is used to set appropriate distribution and parameters. Second, the classification model estimates the probability of the presence of each arc in the optimal solution. Features, which are related to costs and capacity, of each arc are utilized in the classification model. Models created on a subset of generated problems are then tested on the other problems. Finally, the proposed framework is applied to the waste management problem in the Czech Republic. The results of the verification show, that it is possible to remove 95% of arcs without impact on strategic decisions and without significant change of an objective function. The computing time of the reduced problem takes only 7% of the original task.

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Hierarchical optimisation model for waste management forecasting in EU

Cited by 9 publications

References 32 publications

Introductory remarks on the special issue of Optimization and Engineering dedicated to SDEWES 2021 conference

Introductory remarks on the special issue of Optimization and Engineering dedicated to SDEWES 2021 conference

Modelling the impact of legislative interventions on future waste production within territorial division

Network flow problem heuristic reduction using machine learning

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