Psychosocial Perspective

Pires, Ana; Martinho, Graça; Rodrigues, Susana; Gomes, Maria Isabel

doi:10.1007/978-3-319-93200-2_6

Cited by 1 publication

(1 citation statement)

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“…The reverse logistic chain of MSW involves several phases: generation; disposition; collection; treatment; or final disposition. Among these phases, designing pre-collection efficient networks is critical for enhancing sustainability of the whole chain (Pires et al, 2019). To contribute to solving this problem, in this work a comprehensive methodology for the design of a pre-collection network for differentiated waste is applied in real scenarios of the city of Bahía Blanca.…”

Section: Introductionmentioning

confidence: 99%

Application of a methodology to design a municipal waste pre-collection network in real scenarios

et al. 2020

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The design of efficient municipal solid waste (MSW) pre-collection networks can contribute to the global efficiency and sustainability of the reverse logistic chain of MSW in modern cities. With this aim, in this paper a comprehensive methodology that involves making decisions in several stages, from waste fraction classification to the final optimization of waste bins’ location, was applied in two real cases of the city of Bahía Blanca, Argentina. This city, does not have much available data about waste generation and, therefore, an important fieldwork had to be performed for applying this methodology, involving estimating population density per block and waste generation rate per inhabitant, identifying the location of commercial and institutional buildings and also estimating its generation rate, as well as performing a characterization of the MSW from similar studies in the literature and surveys performed to make decisions. The modelling of the urban characteristics was performed in a geographic information system. In the bins’ location problem, a mixed-integer optimization model was applied, seeking to minimize the investment costs, given the maximum area available and the capacity of the bins. Different scenarios were analysed, considering different collection frequencies and the maximum distance to be travelled by the user.

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Section: Introductionmentioning

confidence: 99%