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Household Packaging Waste Management

  • João A. Ferreira
  • Manuel C. FigueiredoEmail author
  • José A. Oliveira
Conference paper
  • 1.4k Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10405)

Abstract

Household packaging waste (HPW) has an important environmental impact and economic relevance. Thus there are networks of collection points (named “ecopontos” in Portugal) where HPW may be deposited for collection by waste management companies.

In order to optimize HPW logistics, accurate estimates of the waste generation rates are needed to calculate the number of collections required for each ecoponto in a given period of time.

The most important factors to estimate HPW generation rates are linked to the characteristics of the population and the social and economic activities around each ecoponto location.

We developed multiple linear regression models and artificial neural networks models to forecast the number of collections per year required for each location. For operational short term planning purposes, these forecasts need to be adjusted for seasonality in order to determine the required number of collections for the relevant planning period. In this paper we describe the methodology used to obtain these forecasts.

Keywords

Forecasting Household packaging waste Waste collection Recycling Seasonality 

Notes

Acknowledgments

This research has been partially supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2013.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • João A. Ferreira
    • 1
    • 2
  • Manuel C. Figueiredo
    • 1
    • 2
    Email author
  • José A. Oliveira
    • 1
    • 2
  1. 1.ALGORITMI Research CentreUniversity of MinhoGuimarãesPortugal
  2. 2.Department of Production and SystemsUniversity of MinhoBragaPortugal

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