O rápido crescimento das regiões urbanas tem impacto significativo nos sistemas de tráfego e transportes. Políticas de gerenciamento e estratégias de planejamento alternativas são claramente necessárias para o tratamento da capacidade limitada, e cada vez mais deficitária, das redes viárias. O conceito de Sistemas Inteligentes de Transportes (ITS) surge neste cenário; mais do que procurar aumentar a capacidade por meio de modificações físicas na infraestrutura, sua premissa baseia-se na utilização de tecnologias avançadas de comunicação e computação para melhor gerir os recursos de tráfego e transportes atuais. Influenciar o padrão do comportamento dos usuários é um desafio que tem estimulado muita pesquisa na área de ITS, onde fatores humanos passam a ter grande importância na modelagem, simulação e avaliação dessa abordagem inovadora. Este trabalho tem como foco a utilização de Sistemas Multiagentes (MAS) na representação dos sistemas de tráfego e transporte, com base nas novasmedidas de desempenho impostas pelas tecnologias ITS. As características de agentes têm grande potencial para representar componentes geográfica e funcionalmente distribuídos, como a maioria dos elementos no domínio da aplicação. Uma arquitetura BDI (beliefs, desires, intentions) é apresentada como alternativa a modelos tradicionais, usados para representar o comportamento do motorista em simulação microscópica, considerando-se a representação explícita dos estados mentais dos usuários. Os conceitos básicos de ITS e MAS são apresentados, assim como exemplos de aplicações relacionados com o tema do trabalho. Esta foi a motivação para a extensão de um simulador microscópico existente, no sentido de incorporar as características dos MAS para melhorar a representação dos motoristas. Assim, a demanda é gerada a partir de uma população de agentes, resultando da decisão sobre a rota e o tempo de partida ao longo de vários dias. O modelo estendido, que passa a suportar a interação de motoristas BDI, foi efetivamente implementado e foram executados diferentes experimentos para testar a abordagem em cenários de tráfego urbano. MAS permite uma abordagem direcionada a processos que facilita a construção de representações modulares, robustas, e extensíveis, características pouco presentes em abordagens voltadas ao resultado. Suas premissas de abstração permitem uma associação direta entre modelo e implementação. Incerteza e variabilidade são assim tratadas de maneira mais intuitiva, uma vez que arquiteturas cognitivas permitem uma fácil representação do comportamento humano na estrutura do motorista. Desta forma, MAS estende a simulação microscópica de tráfego no sentido de melhor representar a complexidade inerente às tecnologias ITS. / The rapid growth of urban areas has a significant impact on traffic and transportation systems. New management policies and planning strategies are clearly necessary to cope with the more than ever limited capacity of existing road networks. The concept of Intelligent Transportation System (ITS) arises in this scenario; rather than attempting to increase road capacity by means of physical modifications to the infrastructure, the premise of ITS relies on the use of advanced communication and computer technologies to handle today’s traffic and transportation facilities. Influencing users’ behaviour patterns is a challenge that has stimulated much research in the ITS field, where human factors start gaining great importance to modelling, simulating, and assessing such an innovative approach. This work is aimed at using Multi-agent Systems (MAS) to represent the traffic and transportation systems in the light of the new performance measures brought about by ITS technologies. Agent features have good potentialities to represent those components of a system that are geographically and functionally distributed, such as most components in traffic and transportation. A BDI (beliefs, desires, and intentions) architecture is presented as an alternative to traditional models used to represent the driver behaviour within microscopic simulation allowing for an explicit representation of users’ mental states. Basic concepts of ITS and MAS are presented, as well as some application examples related to the subject. This has motivated the extension of an existing microscopic simulation framework to incorporate MAS features to enhance the representation of drivers. This way demand is generated from a population of agents as the result of their decisions on route and departure time, on a daily basis. The extended simulation model that now supports the interaction of BDI driver agents was effectively implemented, and different experiments were performed to test this approach in commuter scenarios. MAS provides a process-driven approach that fosters the easy construction of modular, robust, and scalable models, characteristics that lack in former result-driven approaches. Its abstraction premises allow for a closer association between the model and its practical implementation. Uncertainty and variability are addressed in a straightforward manner, as an easier representation of humanlike behaviours within the driver structure is provided by cognitive architectures, such as the BDI approach used in this work. This way MAS extends microscopic simulation of traffic to better address the complexity inherent in ITS technologies.

O rápido crescimento das regiões urbanas tem impacto significativo nos sistemas de tráfego e transportes. Políticas de gerenciamento e estratégias de planejamento alternativas são claramente necessárias para o tratamento da capacidade limitada, e cada vez mais deficitária, das redes viárias. O conceito de Sistemas Inteligentes de Transportes (ITS) surge neste cenário; mais do que procurar aumentar a capacidade por meio de modificações físicas na infraestrutura, sua premissa baseia-se na utilização de tecnologias avançadas de comunicação e computação para melhor gerir os recursos de tráfego e transportes atuais. Influenciar o padrão do comportamento dos usuários é um desafio que tem estimulado muita pesquisa na área de ITS, onde fatores humanos passam a ter grande importância na modelagem, simulação e avaliação dessa abordagem inovadora. Este trabalho tem como foco a utilização de Sistemas Multiagentes (MAS) na representação dos sistemas de tráfego e transporte, com base nas novasmedidas de desempenho impostas pelas tecnologias ITS. As características de agentes têm grande potencial para representar componentes geográfica e funcionalmente distribuídos, como a maioria dos elementos no domínio da aplicação. Uma arquitetura BDI (beliefs, desires, intentions) é apresentada como alternativa a modelos tradicionais, usados para representar o comportamento do motorista em simulação microscópica, considerando-se a representação explícita dos estados mentais dos usuários. Os conceitos básicos de ITS e MAS são apresentados, assim como exemplos de aplicações relacionados com o tema do trabalho. Esta foi a motivação para a extensão de um simulador microscópico existente, no sentido de incorporar as características dos MAS para melhorar a representação dos motoristas. Assim, a demanda é gerada a partir de uma população de agentes, resultando da decisão sobre a rota e o tempo de partida ao longo de vários dias. O modelo estendido, que passa a suportar a interação de motoristas BDI, foi efetivamente implementado e foram executados diferentes experimentos para testar a abordagem em cenários de tráfego urbano. MAS permite uma abordagem direcionada a processos que facilita a construção de representações modulares, robustas, e extensíveis, características pouco presentes em abordagens voltadas ao resultado. Suas premissas de abstração permitem uma associação direta entre modelo e implementação. Incerteza e variabilidade são assim tratadas de maneira mais intuitiva, uma vez que arquiteturas cognitivas permitem uma fácil representação do comportamento humano na estrutura do motorista. Desta forma, MAS estende a simulação microscópica de tráfego no sentido de melhor representar a complexidade inerente às tecnologias ITS. / The rapid growth of urban areas has a significant impact on traffic and transportation systems. New management policies and planning strategies are clearly necessary to cope with the more than ever limited capacity of existing road networks. The concept of Intelligent Transportation System (ITS) arises in this scenario; rather than attempting to increase road capacity by means of physical modifications to the infrastructure, the premise of ITS relies on the use of advanced communication and computer technologies to handle today’s traffic and transportation facilities. Influencing users’ behaviour patterns is a challenge that has stimulated much research in the ITS field, where human factors start gaining great importance to modelling, simulating, and assessing such an innovative approach. This work is aimed at using Multi-agent Systems (MAS) to represent the traffic and transportation systems in the light of the new performance measures brought about by ITS technologies. Agent features have good potentialities to represent those components of a system that are geographically and functionally distributed, such as most components in traffic and transportation. A BDI (beliefs, desires, and intentions) architecture is presented as an alternative to traditional models used to represent the driver behaviour within microscopic simulation allowing for an explicit representation of users’ mental states. Basic concepts of ITS and MAS are presented, as well as some application examples related to the subject. This has motivated the extension of an existing microscopic simulation framework to incorporate MAS features to enhance the representation of drivers. This way demand is generated from a population of agents as the result of their decisions on route and departure time, on a daily basis. The extended simulation model that now supports the interaction of BDI driver agents was effectively implemented, and different experiments were performed to test this approach in commuter scenarios. MAS provides a process-driven approach that fosters the easy construction of modular, robust, and scalable models, characteristics that lack in former result-driven approaches. Its abstraction premises allow for a closer association between the model and its practical implementation. Uncertainty and variability are addressed in a straightforward manner, as an easier representation of humanlike behaviours within the driver structure is provided by cognitive architectures, such as the BDI approach used in this work. This way MAS extends microscopic simulation of traffic to better address the complexity inherent in ITS technologies.

O rápido crescimento das regiões urbanas tem impacto significativo nos sistemas de tráfego e transportes. Políticas de gerenciamento e estratégias de planejamento alternativas são claramente necessárias para o tratamento da capacidade limitada, e cada vez mais deficitária, das redes viárias. O conceito de Sistemas Inteligentes de Transportes (ITS) surge neste cenário; mais do que procurar aumentar a capacidade por meio de modificações físicas na infraestrutura, sua premissa baseia-se na utilização de tecnologias avançadas de comunicação e computação para melhor gerir os recursos de tráfego e transportes atuais. Influenciar o padrão do comportamento dos usuários é um desafio que tem estimulado muita pesquisa na área de ITS, onde fatores humanos passam a ter grande importância na modelagem, simulação e avaliação dessa abordagem inovadora. Este trabalho tem como foco a utilização de Sistemas Multiagentes (MAS) na representação dos sistemas de tráfego e transporte, com base nas novasmedidas de desempenho impostas pelas tecnologias ITS. As características de agentes têm grande potencial para representar componentes geográfica e funcionalmente distribuídos, como a maioria dos elementos no domínio da aplicação. Uma arquitetura BDI (beliefs, desires, intentions) é apresentada como alternativa a modelos tradicionais, usados para representar o comportamento do motorista em simulação microscópica, considerando-se a representação explícita dos estados mentais dos usuários. Os conceitos básicos de ITS e MAS são apresentados, assim como exemplos de aplicações relacionados com o tema do trabalho. Esta foi a motivação para a extensão de um simulador microscópico existente, no sentido de incorporar as características dos MAS para melhorar a representação dos motoristas. Assim, a demanda é gerada a partir de uma população de agentes, resultando da decisão sobre a rota e o tempo de partida ao longo de vários dias. O modelo estendido, que passa a suportar a interação de motoristas BDI, foi efetivamente implementado e foram executados diferentes experimentos para testar a abordagem em cenários de tráfego urbano. MAS permite uma abordagem direcionada a processos que facilita a construção de representações modulares, robustas, e extensíveis, características pouco presentes em abordagens voltadas ao resultado. Suas premissas de abstração permitem uma associação direta entre modelo e implementação. Incerteza e variabilidade são assim tratadas de maneira mais intuitiva, uma vez que arquiteturas cognitivas permitem uma fácil representação do comportamento humano na estrutura do motorista. Desta forma, MAS estende a simulação microscópica de tráfego no sentido de melhor representar a complexidade inerente às tecnologias ITS. / The rapid growth of urban areas has a significant impact on traffic and transportation systems. New management policies and planning strategies are clearly necessary to cope with the more than ever limited capacity of existing road networks. The concept of Intelligent Transportation System (ITS) arises in this scenario; rather than attempting to increase road capacity by means of physical modifications to the infrastructure, the premise of ITS relies on the use of advanced communication and computer technologies to handle today’s traffic and transportation facilities. Influencing users’ behaviour patterns is a challenge that has stimulated much research in the ITS field, where human factors start gaining great importance to modelling, simulating, and assessing such an innovative approach. This work is aimed at using Multi-agent Systems (MAS) to represent the traffic and transportation systems in the light of the new performance measures brought about by ITS technologies. Agent features have good potentialities to represent those components of a system that are geographically and functionally distributed, such as most components in traffic and transportation. A BDI (beliefs, desires, and intentions) architecture is presented as an alternative to traditional models used to represent the driver behaviour within microscopic simulation allowing for an explicit representation of users’ mental states. Basic concepts of ITS and MAS are presented, as well as some application examples related to the subject. This has motivated the extension of an existing microscopic simulation framework to incorporate MAS features to enhance the representation of drivers. This way demand is generated from a population of agents as the result of their decisions on route and departure time, on a daily basis. The extended simulation model that now supports the interaction of BDI driver agents was effectively implemented, and different experiments were performed to test this approach in commuter scenarios. MAS provides a process-driven approach that fosters the easy construction of modular, robust, and scalable models, characteristics that lack in former result-driven approaches. Its abstraction premises allow for a closer association between the model and its practical implementation. Uncertainty and variability are addressed in a straightforward manner, as an easier representation of humanlike behaviours within the driver structure is provided by cognitive architectures, such as the BDI approach used in this work. This way MAS extends microscopic simulation of traffic to better address the complexity inherent in ITS technologies.

An important goal of modern data networks is to support multiple applications over a single network infrastructure. The combination of data, voice, video and conference traffic, each requiring a unique Quality of Service (QoS), makes resource dimensioning a very challenging task. To guarantee QoS by mere over-provisioning of bandwidth is not viable in the long run, as network resources are expensive. The aim of proper resource dimensioning is to provide the required QoS while making optimal use of the allocated bandwidth. Dimensioning parameters used by service providers today are based on best practice recommendations, and are not necessarily optimal. This dissertation focuses on resource dimensioning for the DiffServ network architecture. Four predefined traffic classes, i.e. Real Time (RT), Interactive Business (IB), Bulk Business (BB) and General Data (GD), needed to be dimensioned in terms of bandwidth allocation and traffic regulation. To perform this task, a study was made of the DiffServ mechanism and the QoS requirements of each class. Traffic generators were required for each class to perform simulations. Our investigations show that the dominating Transport Layer protocol for the RT class is UDP, while TCP is mostly used by the other classes. This led to a separate analysis and requirement for traffic models for UDP and TCP traffic. Analysis of real-world data shows that modern network traffic is characterized by long-range dependency, self-similarity and a very bursty nature. Our evaluation of various traffic models indicates that the Multi-fractal Wavelet Model (MWM) is best for TCP due to its ability to capture long-range dependency and self-similarity. The Markov Modulated Poisson Process (MMPP) is able to model occasional long OFF-periods and burstiness present in UDP traffic. Hence, these two models were used in simulations. A test bed was implemented to evaluate performance of the four traffic classes defined in DiffServ. Traffic was sent through the test bed, while delay and loss was measured. For single class simulations, dimensioning values were obtained while conforming to the QoS specifications. Multi-class simulations investigated the effects of statistical multiplexing on the obtained values. Simulation results for various numerical provisioning factors (PF) were obtained. These factors are used to determine the link data rate as a function of the required average bandwidth and QoS. The use of class-based differentiation for QoS showed that strict delay and loss bounds can be guaranteed, even in the presence of very high (up to 90%) bandwidth utilization. Simulation results showed small deviations from best practice recommendation PF values: A value of 4 is currently used for both RT and IB classes, while 2 is used for the BB class. This dissertation indicates that 3.89 for RT, 3.81 for IB and 2.48 for BB achieve the prescribed QoS more accurately. It was concluded that either the bandwidth distribution among classes, or quality guarantees for the BB class should be adjusted since the RT and IB classes over-performed while BB under-performed. The results contribute to the process of resource dimensioning by adding value to dimensioning parameters through simulation rather than mere intuition or educated guessing. / Dissertation (MEng (Electronic Engineering))--University of Pretoria, 2007. / Electrical, Electronic and Computer Engineering / unrestricted

Connected and automated vehicles (CVs and AVs, respectively) are rapidly emerging paradigms aiming to deploy and develop transportation systems that enable automated driving and data exchange among vehicles, infrastructure, and mobile devices to improve mobility, enhance safety, and reduce the adverse environmental impacts of transportation systems. Based on these premises, the focus of this research is to quantify the potential benefits of CVs and AVs to provide insight into how these technologies will impact road users and network performance. To assess the traffic operational performance of CVs, a connectivity-based modeling framework was developed based on traffic microsimulation for a real network in the city of Toronto. Then the effects of real-time routing guidance and advisory warning messages were studied for CVs. In addition, the impact of rerouting of non-connected vehicles (non-CVs) in response to various sources of information, such as mobile apps, GPS or VMS, was considered and evaluated. The results demonstrate the potential of such systems to improve mobility, enhance safety, and reduce greenhouse gas emissions (GHGs) at the network-wide level presented for different CVs market penetration. Additionally, the practical application of CVs in travel time estimation and its relationship with the number and location of roadside equipment (RSE) along freeways was investigated. A methodology was developed for determining the optimal number and location of roadside equipment (RSE) for reducing travel time estimation error in a connected vehicle environment. A simulation testbed that includes CVs was developed and implemented in the microsimulation model for Toronto 400-series highway network. The results reveal that the suggested methodology is capable of optimizing the number and location of RSEs in a connected vehicle environment. The optimization results indicate that the accuracy of travel time estimates is primarily dependent on the location of RSEs and less dependent on the total density of RSEs. In addition to CVs, the potential capacity increase of highways as a function of AVs market penetration was also studied and estimated. AVs are classified into Cooperative and Autonomous AVs. While Autonomous AVs rely only to their detection technology to sense their surroundings, Cooperative AVs, can also benefit from direct communication between vehicles and infrastructure. Cooperative car-following and lane-changing models were developed in a microsimulation model to enable AVs to maintain safe following and merging gaps. This study shows that cooperative AVs can adopt shorter gap than autonomous AVs and consequently, can significantly improve the lane capacity of highways. The achievable capacity increase for autonomous AVs appears highly insensitive to the market penetration, namely, the capacity remains within a narrow range of 2,046 to 2,238 vph irrespective of market penetration. The results of this research provide practitioners and decision-makers with knowledge regarding the potential capacity benefits of AVs with respect to market penetration and fleet conversion. / Thesis / Doctor of Philosophy (PhD)

On étudie dans ce travail des systèmes de lois de conservation hyperboliques. La première partie étudie le temps d'existence des solutions régulières et régulières par morceaux de la dynamique des fluides compressibles. Après avoir présenté l'état de l'art en matière de solutions régulières, on montre une extension d'un théorème de Grassin à des gaz de Van der Waals. On étudie ensuite les solutions ondes de chocs : on poursuit l'approche de T. T. Li pour estimer leur temps d'existence dans le cas isentropique à symétrie sphérique, et l'approche de Whitham afin d'obtenir une équation approchée vérifiée par la surface de discontinuité. Dans une deuxième partie, motivée par la modélisation d'un rond-point en trafic routier, on étudie une extension multi-classe du modèle macroscopique de Lighthill-Whitham-Richards sur une route infinie avec des jonctions. On différencie les véhicules selon leur origine et leur destination et on introduit des conditions aux bords adaptées au niveau des jonctions. On obtient existence et unicité d'une solution au problème de Riemann pour ce modèle. Des simulations numériques attestent que les solutions obtenues existent en temps long. On aborde enfin le problème de Cauchy par la méthode de front tracking. La dernière partie concerne les lois de conservation scalaires. La première question abordée est le contrôle de la variation totale de la solution et la stabilité des solutions faibles entropiques par rapport au flux et à la source. Ce résultat nous permet d'étudier des équations avec flux non-local. Une fois établi leur caractère bien posé, on montre la Gâteaux-différentiabilité du semi-groupe obtenu par rapport aux conditions initiales. / In this work, we study hyperbolic systems of balance laws. The first part is devoted to compressible fluid dynamics, and particularly to the lifespan of smooth or piecewise smooth solutions. After presenting the state of art, we show an extension to more general gases of a theorem by Grassin.We also study shock waves solutions: first, we extend T. T. Li's approach to estimate the time of existence in the isentropic spherical case; second, we develop Whitham's ideas to obtain an approximated equation satisfied by the discontinuity surface. In the second part, we set up a new model for a roundabout. This leads us to study a multi-class extension of the macroscopic Lighthill-Whitham-Richards' model. We study the traffic on an infinite road, with some points of junction. We distinguish vehicles according to their origin and destination and add some boundary conditions at the junctions. We obtain existence and uniqueness of a weak entropy solution for the Riemann problem. As a complement, we provide numerical simulations that exhibit solutions with a long time of existence. Finally, the Cauchy problem is tackled by the front tracking method. In the last part, we are interested in scalar hyperbolic balance laws. The first question addressed is the control of the total variation and the stability of entropy solutions with respect to flow and source. With this result, we can study equations with non-local flow, which do not fit into the framework of classical theorems. We show here that these kinds of equations are well posed and we show the Gâteaux-differentiability with respect to initial conditions, which is important to characterize maxima or minima of a given cost functional.

<p>This thesis, consisting of three papers and a summary, studies topics in the theory of stochastic processes related to long-range dependence. Much recent interest in such probabilistic models has its origin in measurements of Internet traffic data, where typical characteristics of long memory have been observed. As a macroscopic feature, long-range dependence can be mathematically studied using certain scaling limit theorems. </p><p>Using such limit results, two different scaling regimes for Internet traffic models have been identified earlier. In one of these regimes traffic at large scales can be approximated by long-range dependent Gaussian or stable processes, while in the other regime the rescaled traffic fluctuates according to stable ``memoryless'' processes with independent increments. In Paper I a similar limit result is proved for a third scaling scheme, emerging as an intermediate case of the other two. The limit process here turns out to be a non-Gaussian and non-stable process with long-range dependence.</p><p>In Paper II we derive a representation for the latter limit process as a stochastic integral of a deterministic function with respect to a certain compensated Poisson random measure. This representation enables us to study some further properties of the process. In particular, we prove that the process at small scales behaves like a Gaussian process with long-range dependence, while at large scales it is close to a stable process with independent increments. Hence, the process can be regarded as a link between these two processes of completely different nature.</p><p>In Paper III we construct a class of processes locally behaving as Gaussian and globally as stable processes and including the limit process obtained in Paper I. These processes can be chosen to be long-range dependent and are potentially suitable as models in applications with distinct local and global behaviour. They are defined using stochastic integrals with respect to the same compensated Poisson random measure as used in Paper II.</p>

This thesis, consisting of three papers and a summary, studies topics in the theory of stochastic processes related to long-range dependence. Much recent interest in such probabilistic models has its origin in measurements of Internet traffic data, where typical characteristics of long memory have been observed. As a macroscopic feature, long-range dependence can be mathematically studied using certain scaling limit theorems. Using such limit results, two different scaling regimes for Internet traffic models have been identified earlier. In one of these regimes traffic at large scales can be approximated by long-range dependent Gaussian or stable processes, while in the other regime the rescaled traffic fluctuates according to stable ``memoryless'' processes with independent increments. In Paper I a similar limit result is proved for a third scaling scheme, emerging as an intermediate case of the other two. The limit process here turns out to be a non-Gaussian and non-stable process with long-range dependence. In Paper II we derive a representation for the latter limit process as a stochastic integral of a deterministic function with respect to a certain compensated Poisson random measure. This representation enables us to study some further properties of the process. In particular, we prove that the process at small scales behaves like a Gaussian process with long-range dependence, while at large scales it is close to a stable process with independent increments. Hence, the process can be regarded as a link between these two processes of completely different nature. In Paper III we construct a class of processes locally behaving as Gaussian and globally as stable processes and including the limit process obtained in Paper I. These processes can be chosen to be long-range dependent and are potentially suitable as models in applications with distinct local and global behaviour. They are defined using stochastic integrals with respect to the same compensated Poisson random measure as used in Paper II.

This dissertation investigates the development of new Global system for mobile communications (GSM) improvement algorithms used to solve the nondeterministic polynomial-time hard (NP-hard) problem of assigning cells to switches. The departure of this project from previous projects is in the area of the GSM network being optimised. Most previous projects tried minimising the signalling load on the network. The main aim in this project is to reduce the operational expenditure as much as possible while still adhering to network element constraints. This is achieved by generating new network configurations with a reduced transmission cost. Since assigning cells to switches in cellular mobile networks is a NP-hard problem, exact methods cannot be used to solve it for real-size networks. In this context, heuristic approaches, evolutionary search algorithms and clustering techniques can, however, be used. This dissertation presents a comprehensive and comparative study of the above-mentioned categories of search techniques adopted specifically for GSM network improvement. The evolutionary search technique evaluated is a genetic algorithm (GA) while the unsupervised learning technique is a Gaussian mixture model (GMM). A number of custom-developed heuristic search techniques with differing goals were also experimented with. The implementation of these algorithms was tested in order to measure the quality of the solutions. Results obtained confirmed the ability of the search techniques to produce network configurations with a reduced operational expenditure while still adhering to network element constraints. The best results found were using the Gaussian mixture model where savings of up to 17% were achieved. The heuristic searches produced promising results in the form of the characteristics they portray, for example, load-balancing. Due to the massive problem space and a suboptimal chromosome representation, the genetic algorithm struggled to find high quality viable solutions. The objective of reducing network cost was achieved by performing cell-to-switch optimisation taking traffic distributions, transmission costs and network element constraints into account. These criteria cannot be divorced from each other since they are all interdependent, omitting any one of them will lead to inefficient and infeasible configurations. Results obtained further indicated that the search space consists out of two components namely, traffic and transmission cost. When optimising, it is very important to consider both components simultaneously, if not, infeasible or suboptimum solutions are generated. It was also found that pre-processing has a major impact on the cluster-forming ability of the GMM. Depending on how the pre-processing technique is set up, it is possible to bias the cluster-formation process in such a way that either transmission cost savings or a reduction in inter base station controller/switching centre traffic volume is given preference. Two of the difficult questions to answer when performing network capacity expansions are where to install the remote base station controllers (BSCs) and how to alter the existing BSC boundaries to accommodate the new BSCs being introduced. Using the techniques developed in this dissertation, these questions can now be answered with confidence. / Dissertation (MEng)--University of Pretoria, 2008. / Electrical, Electronic and Computer Engineering / unrestricted