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Mixed-integer quadratic optimization for waste flow quantification
The transition to a circular economy can be realized with higher waste recycling. With the knowledge of waste flows and the links between them, it is possible to plan the infrastructure of the entire system and set the goals needed for the transition to a circular economy. If the statistical analysis does not provide quality models, it is possible to describe waste flows using basic balance relationships. This contribution presents an optimization model based on quadratic programming. The output of the model is an estimate of the waste amount that was managed to divert from mixed municipal waste to separate fractions in the past period. A key input is an estimate of the composition of mixed municipal waste. For a more detailed territorial model, composition estimates are often not available, so an optimization model using the principle of credibility has been proposed. Uncertain information for lower territorial units is corrected by aggregated results for the national level. The resulting optimization models were tested on the data of the Czech Republic for the period 2010–2018 in annual detail. The result interprets what part of the newly separated waste comes from mixed municipal waste. For the significant monitored fractions this value is low, 0.26 for bio-waste in the Czech Republic. On the contrary, the high part of the shift from mixed municipal waste is for plastic, 0.82. The results showed the advantage of correction at lower territory levels due to the high variability of the input data.
Mixed-integer quadratic optimization for waste flow quantification
The transition to a circular economy can be realized with higher waste recycling. With the knowledge of waste flows and the links between them, it is possible to plan the infrastructure of the entire system and set the goals needed for the transition to a circular economy. If the statistical analysis does not provide quality models, it is possible to describe waste flows using basic balance relationships. This contribution presents an optimization model based on quadratic programming. The output of the model is an estimate of the waste amount that was managed to divert from mixed municipal waste to separate fractions in the past period. A key input is an estimate of the composition of mixed municipal waste. For a more detailed territorial model, composition estimates are often not available, so an optimization model using the principle of credibility has been proposed. Uncertain information for lower territorial units is corrected by aggregated results for the national level. The resulting optimization models were tested on the data of the Czech Republic for the period 2010–2018 in annual detail. The result interprets what part of the newly separated waste comes from mixed municipal waste. For the significant monitored fractions this value is low, 0.26 for bio-waste in the Czech Republic. On the contrary, the high part of the shift from mixed municipal waste is for plastic, 0.82. The results showed the advantage of correction at lower territory levels due to the high variability of the input data.
Mixed-integer quadratic optimization for waste flow quantification
Optim Eng
Šomplák, R. (author) / Smejkalová, V. (author) / Kůdela, J. (author)
Optimization and Engineering ; 23 ; 2177-2201
2022-12-01
25 pages
Article (Journal)
Electronic Resource
English
Data reconciliation , Mixed-integer quadratic optimization , Data aggregation , Waste production , Mixed municipal waste , Waste flow Mathematics , Optimization , Engineering, general , Systems Theory, Control , Environmental Management , Operations Research/Decision Theory , Financial Engineering , Mathematics and Statistics
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