Stratification modelling for waste variation in different areas

abstract

en

Waste composition is the crucial parameter for targeting policies and promotions in waste management. Areas have a diverse population structure and urban character, which significantly changes the differences in the production of individual types of waste. The differences might be explained by correlated variables, which are unknown and can only be estimated. A long-term survey, which takes into account the variation during the year, should be carried out to obtain estimates of the waste composition. These studies are costly and cannot be performed in all areas. For such purposes, stratification techniques are used to select representative samples to obtain the most accurate results. However, general stratification procedures do not take into account the specificities of waste management, and tailor-made approaches should be proposed. This paper deals with possible approaches and demonstrates them in a case study. In addition to defining the optimal areas for conducting the investigations on waste composition, the output identified fundamental boundaries of the presented problem.

Waste composition is the crucial parameter for targeting policies and promotions in waste management. Areas have a diverse population structure and urban character, which significantly changes the differences in the production of individual types of waste. The differences might be explained by correlated variables, which are unknown and can only be estimated. A long-term survey, which takes into account the variation during the year, should be carried out to obtain estimates of the waste composition. These studies are costly and cannot be performed in all areas. For such purposes, stratification techniques are used to select representative samples to obtain the most accurate results. However, general stratification procedures do not take into account the specificities of waste management, and tailor-made approaches should be proposed. This paper deals with possible approaches and demonstrates them in a case study. In addition to defining the optimal areas for conducting the investigations on waste composition, the output identified fundamental boundaries of the presented problem.

clustering; stratification; waste composition

11.07.2021

978-618-85079-1-3

31st European Conference on Operational Research Conference Handbook

218–218

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