Otimização da recolha de resíduos urbanos : caso de estudo de Aveiro

O elevado custo da operação de recolha de resíduos urbanos e a necessidade de cumprir metas dispostas em instrumentos legais são duas motivações que conduzem à necessidade de otimizar o serviço da recolha de resíduos. A otimização da recolha de resíduos é um problema de elevada complexidade de resolução que envolve a análise de redes de transporte. O presente trabalho propõe soluções de otimização da recolha de resíduos urbanos indiferenciados, a partir de um caso de estudo: o percurso RSU I 06 do município de Aveiro. Para este efeito, recorreu-se a uma aplicação informática de representação e análise geográfica: software ArcGIS denominada ArcMap e sua extensão Network Analyst, desenvolvida para calcular circuitos otimizados entre pontos de interesse. O trabalho realizado de aplicação do Network Analyst inclui a apresentação de duas das suas funcionalidades (Route e Vehicle Routing Problem). Em relação ao atual circuito de recolha e com base nos ensaios efetuados, foi possível concluir que esta aplicação permite obter circuitos de recolha otimizados mais curtos ou com menor duração. Contudo, ao nível da gestão permitiu concluir que, com a atual capacidade de contentorização, seria viável reduzir a frequência de recolha de seis vezes por semana para metade, dividindo a área de recolha em duas áreas, de acordo com as necessidades de cada local, reduzindo ainda mais o esforço de recolha. A aplicação do Network Analyst ao caso de estudo, permitiu concluir que é um software com muito interesse no processo de gestão da recolha de resíduos urbanos, apesar de apresentar algumas restrições de aplicação e que a qualidade/eficácia do procedimento de otimização depende da qualidade dos dados de entrada, em particular do descritivo geográfico disponível para os arruamentos e, em larga medida, também depende do modelo de gestão considerado.

Exact solutions to the short sea shipping distribution problem

Short sea shipping has several advantages over other means of transportation, recognized by EU members. The maritime transportation could be dealt like a combination of two well-known problems: the container stowage problem and routing planning problem. The integration of these two well-known problems results in a new problem CSSRP (Container stowage and ship routing problem) that is also an hard combinatorial optimization problem. The aim of this work is to solve the CSSRP using a mixed integer programming model. It is proved that regardless the complexity of this problem, optimal solutions could be achieved in a reduced computational time. For testing the mathematical model some problems based on real data were generated and a sensibility analysis was performed.

Impact of node mobility in user-centric routing

Recent paradigms in wireless communication architectures describe environments where nodes present a highly dynamic behavior (e.g., User Centric Networks). In such environments, routing is still performed based on the regular packet-switched behavior of store-and-forward. Albeit sufficient to compute at least an adequate path between a source and a destination, such routing behavior cannot adequately sustain the highly nomadic lifestyle that Internet users are today experiencing. This thesis aims to analyse the impact of the nodes’ mobility on routing scenarios. It also aims at the development of forwarding concepts that help in message forwarding across graphs where nodes exhibit human mobility patterns, as is the case of most of the user-centric wireless networks today. The first part of the work involved the analysis of the mobility impact on routing, and we found that node mobility significance can affect routing performance, and it depends on the link length, distance, and mobility patterns of nodes. The study of current mobility parameters showed that they capture mobility partially. The routing protocol robustness to node mobility depends on the routing metric sensitivity to node mobility. As such, mobility-aware routing metrics were devised to increase routing robustness to node mobility. Two categories of routing metrics proposed are the time-based and spatial correlation-based. For the validation of the metrics, several mobility models were used, which include the ones that mimic human mobility patterns. The metrics were implemented using the Network Simulator tool using two widely used multi-hop routing protocols of Optimized Link State Routing (OLSR) and Ad hoc On Demand Distance Vector (AODV). Using the proposed metrics, we reduced the path re-computation frequency compared to the benchmark metric. This means that more stable nodes were used to route data. The time-based routing metrics generally performed well across the different node mobility scenarios used. We also noted a variation on the performance of the metrics, including the benchmark metric, under different mobility models, due to the differences in the node mobility governing rules of the models.