A aplicação de redes sem fio vem crescendo consideravelmente nos últimos anos. Protocolos baseados nesta tecnologia estão sendo desenvolvidos para uma grande variedade de aplicações. A confiabilidade é um dos principais requisitos dos protocolos de comunicação nos ambientes industriais. Interferências, ambiente ruidoso e o grande risco das aplicações industriais que são monitoradas são fatores que elevam os níveis de exigência no que se refere à confiabilidade, redundância e segurança do protocolo. O protocolo WirelessHART é um padrão de comunicação sem fio desenvolvido especificamente para monitoramento e controle de processos com os requisitos necessários para ser utilizado em ambientes industriais. A norma do WirelessHART define diversos aspectos técnicos a serem utilizados no desenvolvimento de algoritmos. Os algoritmos de roteamento e escalonamento de mensagens são de grande relevância para o cumprimento dos requisitos temporais, de confiabilidade e segurança. Requisitos de roteamento e escalonamento são especificados, porém, os algoritmos a serem utilizados não são definidos. O objetivo nessa dissertação é analisar alguns dos principais algoritmos que tem sido propostos especificamente para o protocolo WirelessHART e apresentar um conjunto capaz de ser aplicado nesse protocolo. Análises e comparações entre os algoritmos são realizadas proporcionando um estudo aprofundado sobre seus impactos no desempenho do protocolo. / The application of wireless networks has grown considerably in recent years. Protocols based on this technology are being developed for a great variety of applications. Reliability is one of the main requirements for communication protocols in industrial environments. Interferences, noisy environment and high risk processes that are monitored are factors that increase the levels of requirements in terms of reliability, redundancy and security of the protocol. The WirelessHART protocol is a wireless communication standard specifically designed for process monitoring and control applications with the necessary requirements for to be used in industrial environments. The WirelessHART standard defines several technical aspects to be used in the development of the algorithms. The algorithms of routing and scheduling messages are highly relevant to meeting the timing requirements of reliability and safety. Routing and scheduling strategies are specified, however, the routing and scheduling algorithms are not defined for use. The goal of this dissertation is to analyze some of the main algorithms that have been proposed specifically for the WirelessHART protocol and to present a set able to be applied in this protocol. Analyzes and comparisons between algorithms are realized by providing a detailed study of their impacts on the protocol performance.

[pt] A indústria das comunicações tem passado nos últimos anos, mundialmente, por profundas transformações. A Internet é a responsável pela maior destas transformações. Com o advento da Internet, existe a necessidade de uma banda de transmissão maior para o tráfego de dados. Para resolver esse problema, surgiu o conceito de redes ópticas e a multiplexação no domínio do comprimento de onda. Entretanto, isso criou um outro problema: o roteamento dos pacotes. A maior parte das redes de comunicação hoje em dia, ainda possui muitos sinais eletrônicos, o que significa que os sinais ópticos precisam ser convertidos em elétricos para serem ampliados, regenerados ou roteados e, depois, reconvertidos para ópticos. Isso acaba gerando atrasos na transmissão dos sinais e um gargalo nas redes ópticas. Para minimizar este problema, vários algoritmos foram criados. Apegando-se a tais fatos, este estudo explora o tema para implementar um algoritmo de enumeração recursiva, que tem como objetivo alocação de comprimentos em redes ópticas, visando minimizar o custo total de transmissão. Esse algoritmo foi testado e comparado com o algoritmo de programação linear, que fornece a solução ótima. / [en] The communication industry was passing in lastest years by great transformations in world. Internet is the mainly responsable for that, because there is the necessity of a large band to data transmission. The optical networks concept and wavelength division multiplexing technology were arised in order to solve this problem. However, this created another problem: the packet routing. The major part of communications networks still has electronics signals. This means that the optical signals have to be converted into electrical signals to be amplified, regenerated and routed and later recovered into optical. This implies in a delay on the data transmission and creates a bottleneck in the optical networks. Some algorithms have been created to minimize this problem. This dissertation has tried to develop an algorithm to solve RWA (routing and wavelength assignment) problems, aiming at the minimum total cost to transmitt datas. This algorithm was tested and compared with the linear program algorithm that gives the optimal solution to RWA problem.

Apesar de serem utilizados com sucesso em problemas de roteirização clássicos como o do caixeiro-viajante e o de roteirização de veículos com janelas de tempo, os algoritmos genéticos não apresentavam bons resultados nos problemas de roteirização de veículos sem janelas de tempo. Utilizando-se de uma tendência recente de hibridização de algoritmos genéticos, Prins (2004) elaborou um algoritmo para o problema de roteirização de veículos sem janelas de tempo, monoperíodo, e que obrigatoriamente atenda a todos os clientes cujos resultados, quando aplicado a instâncias de Christofides et al. (1979) e de Golden et al. (1998), são comparáveis aos melhores códigos elaborados com base na busca tabu. Diferentemente da maioria dos algoritmos genéticos apresentados para solução de problemas de roteirização de veículos, no método desenvolvido por Prins (2004) o cromossomo é composto apenas pelos pontos a serem atendidos, não contendo delimitadores de rotas. Estas são definidas a partir de um método de particionamento do cromossomo. Este trabalho implementa o algoritmo descrito por Prins (2004) e propõe a este melhorias em diversas de suas etapas, como inicialização, operação de crossover, operação de mutação, reinicialização e particionamento do cromossomo. As alterações implantadas são aplicadas às instâncias de Christofides et al. (1979) e comparadas com o algoritmo inicial em termos de qualidade de solução e tempo de processamento. Finalmente, é elaborado um algoritmo genético que contempla as alterações que obtiveram resultados positivos. / In the Vehicle Routing Problem (VRP) we seek for a set of minimum-cost vehicle routes for a fleet of identical vehicles, each starting and ending at a depot, such that each customer is visited exactly once and the total demand of any route does not exceed the vehicle capacity. Several families of heuristics have been proposed for the VRP. They can be broadly classified into two main classes: classical heuristics developed between 1960 and 1990, and, more recently, metaheuristics. Among them, tabu search plays an key role, being acknowledged by most authors as the most successful approach for the VRP. In the literature some successful implementations of metaheuristic Genetic Algorithm (GA) can be found for classic routing problems such as the traveling salesman and vehicle routing problems with time windows. However, until recently, the same did not apply for the VRP. In this thesis we develop a genetic algorithm without trip delimiters, and hybridized with a local search procedure, for the solving the VRP, which is based on the work of Prins (2004). At any time, a chromosome can be converted into an optimal VRP solution (subject to chromosome sequence) by means of a splitting procedure, in which the chromosome sequence, representing a giant tour, is partitioned into feasible routes in terms of vehicle capacities. Starting with the procedure originally proposed Prins (2004), we then introduce new improvements in terms of the different components of the GA, aiming to obtain improved solutions. These include how we determine the initial population, different partitioning approaches, alternative reproduction (crossover) processes, a granular tabu mechanism similar to the one proposed by Toth and Vigo (2003 and, finally, in changes in the reinitialization process, aiming to reestablish diversity. Computational experiments are presented, based on the 14 classical Christofides instances for the VRP. The results show that the proposed improved versions of the GA allow us to obtain better solutions when compared to the original approach by Prins (2004).

Ces deux dernières décennies les systèmes P2P de partage de fichiers sont devenus très populaires grâce aux accès à des ressources diverses, distribuées sur Internet. Parallèlement à l'évolution de cette catégorie de systèmes, les dispositifs mobiles (téléphones cellulaires, PDA et autres appareils portatifs) ont eu un grand succès sur le marché. Équipés d'une technologie de communication sans fil (Bluetooth, et Wifi), ils peuvent communiquer sans nécessiter une infrastructure particulière en utilisant un réseau mobile adhoc (Mobile Adhoc NETwork -MANET). De la même manière, les systèmes P2P peuvent être aussi déployés sur ce type de réseau et deviennent des systèmes P2P mobiles (Mobile 2P systems). Dans le cadre de cette thèse, nous nous intéressons essentiellement à la recherche d'information dans les systèmes P2P et plus précisément au problème de routage de requêtes. La première partie de la thèse, s'est focalisée sur le routage de requêtes dans les systèmes P2P sur Internet. Nous avons proposé (i) un modèle de routage sémantique basé sur l'historique des requêtes. Ce modèle est ensuite instancié pour définir une nouvelle méthode de routage par apprentissage. Pour pallier le problème de démarrage à froid, (ii) nous avons proposé une méthode prédictive de l'intention de l'utilisateur qui construit une base de connaissances à priori pour chaque pair. Enfin, (iii) nous avons proposé une méthode de routage hybride pour traiter le problème d'échec de sélection. Cette méthode est basée sur l'historique des requêtes et le regroupement de pairs dans des groupes sémantiques. La deuxième partie de la thèse, s'est focalisée sur le routage de requêtes dans les systèmes P2P mobiles. L'apparition des MANETs, a soulevé de nouveaux challenges de routage. Ces réseaux souffrent de plusieurs contraintes liées aux supports de transmission ou bien aux dispositifs mobiles. Dans ce cadre, nous avons proposé une méthode de routage pour les systèmes P2P non structurés mobiles basée sur le contexte de l'utilisateur. D'un point de vue technique, toutes ces propositions ont été développées, validées et évaluées grâce aux simulateurs PeerSim et NS2 / Peer-to-peer systems have emerged as platforms for users to search and share information over the Internet. In fact, thanks to these systems, user can share various resources, send queries to search and locate resources shared by other users. Nowadays, mobile and wireless technology has achieved great progress. These devices are also equipped with low radio range technology, like Bluetooth and Wi-Fi, etc. By means of the low radio range technology, they can communicate with each other without using communication infrastructure (e.g. Internet network) and form a mobile ad hoc network (MANET). Hence, P2P file sharing systems can be also deployed over MANET. A challenging problem in unstructured P2P systems is query routing. Researches' efficiency and effectiveness can be improved by making smart decisions for query routing. Our contributions, in this thesis, focus on two complementary axes. Firstly, our research work focalized on P2P systems over Internet. We introduced a novel semantic model for query routing based on past queries, thereafter we instantiated this model to define our specific routing method. In addition, we addressed two difficult challenging problems: (i) the bootstraping (ii) the unsuccessful relevant peers search. Secondly, we are focalized on P2P systems over MANET. Due the nature of MANET, mobile P2P systems suffer from several constraints of wireless medium and energy-limited. Indeed, query routing methods proposed for P2P system over Internet cannot be applied. In this context, we proposed a context-aware integrated routing method for P2P file sharing systems over MANET. The different contributions are developed, validated and evaluated with the network simulators PeerSim and NS2

In IP networks using the OPSF-principle together with the ECMP-principle, thetraffic is routed in all shortest paths. Weights on links are set by an administrator,not knowing how the resulting routing pattern will become. In this final thesis, I givea heuristic solution to the problem of changing a set of desired routing patterns inan ordered way to make them compatible with each other. An implementation of thealgorithm has been made and some testing with provided data for performance is alsopresented.

Agricultural producers consider utilizing multiple machines to reduce field completion times for improving effective field capacity. Using a number of smaller machines rather than a single big machine also has benefits such as sustainability via less compaction risk, redundancy in the event of an equipment failure, and more flexibility in machinery management. However, machinery management is complicated due to logistics issues. In this work, the allocation and ordering of field paths among a number of available machines have been transformed into a solvable Vehicle Routing Problem (VRP). A basic heuristic algorithm (a modified form of the Clarke-Wright algorithm) and a meta-heuristic algorithm, Tabu Search, were employed to solve the VRP. The solution considered optimization of field completion time as well as improving the field efficiency. Both techniques were evaluated through computer simulations with 2, 3, 5, or 10 vehicles working simultaneously to complete the same operation. Furthermore, the parameters of the VRP were changed into a dynamic, multi-depot representation to enable the re-route of vehicles while the operation is ongoing. The results proved both the Clarke-Wright and Tabu Search algorithms always generated feasible solutions. The Tabu Search solutions outperformed the solutions provided by the Clarke-Wright algorithm. As the number of the vehicles increased, or the field shape became more complex, the Tabu Search generated better results in terms of reducing the field completion times. With 10 vehicles working together in a real-world field, the benefit provided by the Tabu Search over the Modified Clarke-Wright solution was 32% reduction in completion time. In addition, changes in the parameters of the VRP resulted in a Dynamic, Multi-Depot VRP (DMDVRP) to reset the routes allocated to each vehicle even as the operation was in progress. In all the scenarios tested, the DMDVRP was able to produce new optimized routes, but the impact of these routes varied for each scenario. The ability of this optimization procedure to reduce field work times were verified through real-world experiments using three tractors during a rotary mowing operation. The time to complete the field work was reduced by 17.3% and the total operating time for all tractors was reduced by 11.5%. The task of a single large machine was also simulated as a task for 2 or 3 smaller machines through computer simulations. Results revealed up to 11% reduction in completion time using three smaller machines. This time reduction improved the effective field capacity.

TCP was conceived to ensure reliable node-to-node communication in moderate-bandwidth, moderate-latency, WANs. As it is now a mature Internet standard, it is the default connection-oriented protocol in networks built from commodity components, including Internet data centers. Data centers, however, rely on high-bandwidth, low-latency networks for communication. Moreover, their communication patterns, especially those generated by distributed applications such as MapReduce, often take the form of synchronous multi-node to node bursts. Under the right conditions, the network switch buffer overflow losses induced by these bursts confuse TCP's feedback mechanisms to the point that TCP throughput collapses. This collapse, termed TCP Incast, results in gross underutilization of link capacities, significantly degrading application performance. Conventional approaches to mitigating Incast have focused on single-path solutions, for instance, adjusting TCP's receive windows and timers, modifying the protocol itself, or adopting explicit congestion notifications. This thesis explores complementary multi-path approaches to avoiding Incast's onset. The principal idea is to use the regularity and high connectivity of typical data center networks, such as the increasingly popular fat-tree topology, to better distribute multi-node to node bursts across the available paths, thereby avoiding the switch buffer overflows that induce TCP Incast. The thesis's main contributions are: (1) development of new oblivious, multi-path, routing schemes for fat-tree networks, (2) derivation of relations between the schemes and Incast's onset, and (3) investigation of a novel "front-back" approach to minimizing the packet reordering introduced by multipath routing. Formal analyses are focused on relating schemes' worst-case loading of certain network resources - expressed as oblivious performance ratios (OPRs) - to Incast's onset. Potential benefits are assessed through ns-3 simulations on fat-trees under a variety of communication patterns. Results indicate that over a variety of experimental conditions, the proposed schemes reduce the incidence of TCP Incast compared to standard routing schemes.

When a package is shipped, the customer often requires the delivery to be made within a particular time window or by a deadline. However, meeting such time requirements is difficult, and delivery companies may not always know ahead of time which customers will need a delivery. In this thesis, we present models and solution approaches for two stochastic last-mile delivery problems in which customers have delivery time constraints and customer presence is known in advance only according to a probability distribution. Our solutions can help reduce the operational costs of delivery while improving customer service. The first problem is the probabilistic traveling salesman problem with time windows (PTSPTW). In the PTSPTW, customers have both a time window and a probability of needing a delivery on any given day. The objective is to find a pre-planned route with an expected minimum cost. We present computational results that characterize the PTSPTW solutions. We provide insights for practitioners on when solving the PTSPTW is beneficial compared to solving the deterministic analogue of the problem. The second problem is the same-day delivery problem (SDDP). The SDDP is a dynamic and stochastic pick-up and delivery problem. In the SDDP, customers make delivery requests throughout the day and vehicles are dispatched from a warehouse or brick and mortar store to serve the requests. Associated with each request is a request deadline or time window. In order to make better-informed decisions, our solution approach incorporates information about future requests into routing decisions by using a sample scenario planning approach with a consensus function. We also introduce an analytical result that identifies when it is beneficial for vehicles to wait at the depot. We present a wide range of computational experiments that demonstrate the value of our approaches.

Data-driven decision making has become more popular in today’s businesses including logistics and vehicle routing. Leveraging historical data, companies can achieve goals such as customer satisfaction management, scalable and efficient operation, and higher overall revenue. In the management of customer satisfaction, logistics companies use consistent assignment of their drivers to customers over time. Creating this consistency takes time and depends on the history experienced between the company and the customer. While pursuing this goal, companies trade off the cost of capacity with consistency because demand is unknown on a daily basis. We propose concepts and methods that enable a parcel delivery company to balance the trade-off between cost and customer satisfaction. We use clustering methods that use cumulative historical service data to generate better consistency using the information entropy measure. Parcel delivery companies route many vehicles to serve customer requests on a daily basis. While clustering was important to the development of early routing algorithms, modern solution methods rely on metaheuristics, which are not easily deployable and often do not have open source code bases. We propose a two-stage, shape-based clustering approach that efficiently obtains a clustering of delivery request locations. Our solution technique is based on creating clusters that form certain shapes with respect to the depot. We obtain a routing solution by ordering all locations in every cluster separately. Our results are competitive with a state-of-the-art vehicle routing solver in terms of quality. Moreover, the results show that the algorithm is more scalable and is robust to problem parameters in terms of runtime. Fish trawling can be considered as a vehicle routing problem where the main objective is to maximize the amount of fish (revenue) facing uncertainty on catch. This uncertainty creates an embedded prediction problem before deciding where to harvest. Using previous catch data to train prediction models, we solve the routing problem a fish trawler faces using dynamically updated routing decisions allowing for spatiotemporal correlation in the random catch. We investigate the relationship between the quality of predictions and the quality of revenue generated as a result.

This dissertation explores workforce planning in manufacturing and healthcare systems. In manufacturing systems, the existing workforce planning models often lack fidelity with respect to the mechanism of learning. Learning refers to that employees’ productivity increases as they gain more experience. Workforce scheduling in the short term has a longer term impact on organizations’ capacity. The mathematical representations of learning are usually nonlinear. This nonlinearity complicates the planning models and provides opportunities to develop solution methodologies for realistically-sized instances. This research formulates the workforce planning problem as a mixed-integer nonlinear program (MINLP) and overcomes the limitations of cur- rent solution methods. Specifically, this research develops a reformulation technique that converts the MINLP to a mixed integer linear program (MILP) and proposes several techniques to speed up the solution time of solving the MILP. In organizations that use group work, workers learn not only by individual learning but also from knowledge transferred from team members. Managers face the decision of how to pair or team workers such that organizations benefit from this transfer of learning. Using a mathematical representation that incorporates both in- dividual learning and knowledge transfer between workers, this research considers the problem of grouping workers to teams and assigning teams to sets of jobs based on workers’ learning and knowledge transfer characteristics. This study builds a Mixed- integer nonlinear programs (MINP) for parallel systems with the objective of maximizing the system throughput and propose exact and heuristic solution approaches for solving the MINLP. In healthcare systems, we focus on managing medical technicians in medical laboratories, in particular, the phlebotomists. Phlebotomists draw specimens from patients based on doctors’ orders, which arrive randomly in a day. According to the literature, optimizing scheduling and routing in hospital laboratories has not been regarded as a necessity for laboratory management. This study is motivated by a real case at University of Iowa Hospital and Clinics, where there is a team of phlebotomists that cannot fulfill doctors requests in the morning shift. The goal of this research is routing these phlebotomists to patient units such that as many orders as possible are fulfilled during the shift. The problem is a team orienteering problem with stochastic rewards and service times. This research develops an a priori approach which applies a variable neighborhood search heuristic algorithm that improves the daily performance compared to the hospital practice.