Otimização logística da poluição de rotas de veículos no transporte de resíduos sólidos urbanos

• Ano de defesa: 2022
• Autor(a) principal: Rezende, Gabriel Henrique Carvalho
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Uberlândia; Brasil; Programa de Pós-graduação em Engenharia Civil
• Palavras-chave em Português: Problema de roteirização de poluição; Roteirização Logística; Resíduos sólidos urbanos; Sistemas de Informações Geográficas; Softwares Livres; CNPQ::ENGENHARIAS::ENGENHARIA CIVIL; Engenharia Civil; Homem - Efeito do meio ambiente; Ar - Poluição; Toxicologia ambiental
• Link de acesso: https://repositorio.ufu.br/handle/123456789/36269; http://doi.org/10.14393/ufu.di.2022.550

This work considers a complex logistics routing issue about vehicle pollution, which is connected to the Pollution Routing Problem (PRP). In the PRP, the direct fuel costs and the resulting Greenhouse Gas (GHG) emissions depend on the distance traveled, on the road slopes, and finally, on the speed of a heavy-duty vehicle. In order to solve this problem, a study of the routing for the urban solid waste (USW) collection was carried out in the Miraporanga district, managed by the municipality of Uberlândia, Brazil. Thus, by using free software in a GIS environment, this paper considers to optimize the waste collection routes in order to minimize GHG emissions into the atmosphere. Because it is a complex problem with multifactorial checks in the logistics study, a Process Hierarchy Analysis (AHP) was developed with the functionality to rank the project variables. During the development of the research, a mathematical equation was formulated to estimate the implementation cost (IC) for a USW collection service according to its logistical variables. Related to route optimization, algorithms inserted into QGIS software were used so as to determine the shortest distance path. The results indicated that there was a reduction of 8.31% in GHG emissions per collection. As for the optimization of the PRP, a reduction of 16.44% in fuel consumption was verified, in terms of distance, speed, payload and road slopes