Genetic Algorithm for Waste Collection in Smart Cities: case of Campolide

Research output: ThesisMaster's Thesis


Smarts cities are becoming an important concept in the cities, it tries to discover methods to interact with the environment in sustainable ways inside urban areas. This concept emerged to deal with the growing urbanization faced by the cities around the globe. Within problems brought by the urbanization, waste management is one of the hardest and most impactful. The collection stage of the waste management is the costliest and the route planning for the garbage trucks is a well-known hard problem. In this project, a genetic algorithm is proposed to deal with the waste collection routing problem using a heterogeneous fleet of trucks. As the population in the city is expected to grow over the years, the project adapts to the current state of the city, because it uses the concept of open data from the municipality to feed itself with the garbage collection information and generate its results. Multiple runs were performed to define its parameters. The algorithm was tested in the simplified real case of Campolide, in the municipality of Lisbon, and proved to be feasible for application on real-world scenarios relying only on actual data of the cities’ waste collection.
Original languageEnglish
QualificationMaster of Science
Awarding Institution
  • NOVA Information Management School (NOVA IMS)
  • Neto, Miguel de Castro, Supervisor
Award date20 Dec 2018
Publication statusPublished - 20 Dec 2018


  • Arc Routing Problem
  • Genetic Algorithm
  • Smart Cities
  • Waste Management


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