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pp 1–35 | Cite as

Reducing pollutant emissions in a waste collection vehicle routing problem using a variable neighborhood tabu search algorithm: a case study

  • Jose Carlos MolinaEmail author
  • Ignacio Eguia
  • Jesus Racero
Original Paper
  • 34 Downloads

Abstract

This paper focuses on designing waste collection routes with a single landfill using eco-efficiency as a performance indicator. In this problem, there are a limited number of heterogeneous vehicles based at a single depot. Empty vehicles leave the depot, collect waste from a set of locations and drop off the collected waste at a specific landfill. Then, vehicles leave the landfill and may collect more waste from other locations or return empty to the depot. Traditional performance indicators in vehicle routing problems are mainly focused on economic objectives, not explicitly considering environmental issues. In this paper, a mathematical model is presented with an eco-efficient objective function that takes into account external costs (climate change and air pollution). The COPERT model is used for estimating fuel consumption, carbon dioxide and pollutant emissions. The problem is first heuristically solved using a semi-parallel construction algorithm. Then, solutions are improved by a variable neighborhood tabu search algorithm developed for this problem. The algorithm is validated for a real problem in the municipality of Alcalá de Guadaíra, within the metropolitan area of Seville (Spain). Results obtained on a set of case studies improve the solution that is currently implemented in the municipality, in terms of total distance traveled, carbon dioxide emissions and pollutant emissions.

Keywords

Waste collection vehicle routing problem Variable neighborhood tabu search COPERT model equations Pollutant emissions 

Mathematics Subject Classification

90B06 (Transportation logistics) 90C11 (Mixed-integer programming) 90C59 (Approximation methods and heuristics) 

Notes

Acknowledgements

This research has been fully funded by the Andalusia Government through Grant P10-TEP-6332.

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Copyright information

© Sociedad de Estadística e Investigación Operativa 2019

Authors and Affiliations

  1. 1.Escuela Superior de IngenieríaUniversidad de SevillaSevilleSpain

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