Waste Collection Point Location and Allocation Model with Hierarchical Clustering

abstract

en

Recycling is a crucial part of environmental sustainability, and the European Union sets regulations and waste recovery targets that should be met in the near future. The cities face the challenge of optimizing investments into waste management to meet the EU standards while maintaining economic affordability. One of the issues is the optimal collection points location for specialized waste that is still not properly recycled (e.g., fat and cooking oil containers, metallic waste containers). The main target is to find the lowest number of collection points that would still attain the waste production, and the average walking distance to the waste container would be kept beneath the tolerable distance for citizens. The population density and waste production vary over city parts, and thus, the need for specialized containers in more populated city centers, industrial zones, or household streets varies as well. The purpose of this work is to develop a robust generalized decision-support tool for waste collection points location and allocation. This task leads to a mixed-integer linear program which would be unsolvable for larger cities in a reasonable time. Therefore, hierarchical clustering is utilized for simplification of the model, and the resulting framework is tested on several case studies – waste allocation for county seats of the Czech Republic.

Recycling is a crucial part of environmental sustainability, and the European Union sets regulations and waste recovery targets that should be met in the near future. The cities face the challenge of optimizing investments into waste management to meet the EU standards while maintaining economic affordability. One of the issues is the optimal collection points location for specialized waste that is still not properly recycled (e.g., fat and cooking oil containers, metallic waste containers). The main target is to find the lowest number of collection points that would still attain the waste production, and the average walking distance to the waste container would be kept beneath the tolerable distance for citizens. The population density and waste production vary over city parts, and thus, the need for specialized containers in more populated city centers, industrial zones, or household streets varies as well. The purpose of this work is to develop a robust generalized decision-support tool for waste collection points location and allocation. This task leads to a mixed-integer linear program which would be unsolvable for larger cities in a reasonable time. Therefore, hierarchical clustering is utilized for simplification of the model, and the resulting framework is tested on several case studies – waste allocation for county seats of the Czech Republic.

optimal location;collection point; clustering;allocation problem

11.07.2021

978-618-85079-1-3

31st European Conference on Operational Research Conference Handbook

126–126

1