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An efficient route design for solid waste collection using graph theory and the algorithm of the traveling agent in dynamic programming.

Moisés Filiberto Mora MurilloWalter Alfredo Mora MurilloLuis Xavier Orbea HinojosaArlys Michel Lastre AleagaGabriel Estuardo Cevallos UveMarc Jorba CuscóDigvijay Pandey
Published in: Environmental monitoring and assessment (2021)
In Santo Domingo de los Tsa'chilas province, Ecuador, the population grows proportionally to the territorial extension in urban and rural parishes; therefore, the conception of domestic solid waste has increased exponentially. In this context, in recent years, the distribution of routes for waste collection has not been dealt with or technically explored. The research objective is to apply the theory of graphs to the sector and use the exact method of the Travel Agent Problem (TSP) in dynamic programming to generate optimal routes by sectors. In addition to measuring the variables longitudinally, we test the researcher's hypothesis using parametric techniques for independent samples in the variable's travel time and distance between the usual route and the new route in the Río Verde parish of Santo Domingo Canton.
Keyphrases
  • heavy metals
  • south africa
  • sewage sludge
  • municipal solid waste
  • life cycle
  • machine learning
  • deep learning
  • neural network
  • risk assessment
  • convolutional neural network
  • density functional theory
  • molecular dynamics