This thesis explores how multi-agent-based simulation can be used for transport policy analysis. Transport policies are often used as a means to reach governmental goals, such as environmental targets to reduce the impact of transportation. To predict how transportation is influenced by policies, public authorities often make use of simulation models. A structured review of such models is made focussing on important transport chain characteristics. We argue that to properly predict the actual environmental, economic, and logistical effects of transport policies, the logistical decisions made in transport chains must be modelled appropriately. Such decisions, e.g., concern the choice of producer and traffic mode, planning of transportation, production, and terminal handling. The review concludes that models currently used for transport policy analysis fail to capture many of these characteristics. We argue that agent-based models have the potential to include these aspects since they are able to explicitly model the actual decision making in transport chains. We have identified a set of generic roles in transport chains where each role is responsible for certain decisions. A multi-agent-based simulator, TAPAS, has been developed in which these roles are modelled as agents. Thus, the decision making in transport chains and its influence by the application of transport policies are captured. The decisions lead to the execution of the logistical operations which in turn have consequences on the logistics, economic, and environmental performance. The usage of TAPAS is illustrated by presenting two scenarios based on realworld transport chains. Simulation experiments of the scenarios have been performed where different types of transport policies are introduced. The simulation results are analysed, e.g., by comparing the results to similar studies and by sensitivity analysis of input parameters. To facilitate the validation and generalisation of simulation results we suggest making use of typical transport chains and roles characterised by, e.g., product type and geographical locations. The type of studies that TAPAS can support are described and compared to studies typically made with traditional models. Transport policies which are relevant to examine are described and their potential influence on transport chains are analysed. The possible usage of TAPAS is discussed and related to different types of users. Public authorities can, e.g., use TAPAS to complement studies using traditional models. This can improve the accuracy of the simulation results by the inclusion of more logistical aspects. Large companies are another type of user which, e.g., can use TAPAS to analyse new market segments, such as new product types or new consumers, where historical data is not available.

Empresas em cadeias de suprimentos têm como objetivo maximizar suas produtividades, e consequentemente seus lucros. Uma maneira de estudar o comportamento destas cadeias é simulá-las utilizando uma abordagem multi-agentes. Neste trabalho, adicionamos múltiplos agentes nos níveis de um modelo amplamente adotado na literatura, denominado Beer Game, para avaliar a eficiência local e global dos fornecedores. Para tal, utilizamos perfis distintos baseados em confiança ou em preço. Medimos o impacto de usar tais políticas de seleção no capital acumulado pelos agentes, e concluímos que as parcerias baseadas em confiança são recomendáveis em cenários com ampla disseminação de informações verdadeiras, enquanto que as baseadas em lucro são mais vantajosas em cenários marcados por pouca comunicação ou pelo espalhamento de informações falsas. / Companies in supply chains have the objective of maximizing their productivities, and consequently their profits. A way of to study the behavior of these chains is to simulate them using a multi-agent-based approach. In this work, we added multiple agents at the levels of a widely adopted model in the literature, called Beer Game, to evaluate the local and global performance of suppliers. To do this, we use distinct profiles based on trust or price. We measure the impact of using such selection policies on the agents\' profit, and we could conclude that trust-based partnerships are recommended in scenarios with wide dissemination of true information, while profit-based partnerships are most advantageous in scenarios marked by poor communication or spreading false information.

Empresas em cadeias de suprimentos têm como objetivo maximizar suas produtividades, e consequentemente seus lucros. Uma maneira de estudar o comportamento destas cadeias é simulá-las utilizando uma abordagem multi-agentes. Neste trabalho, adicionamos múltiplos agentes nos níveis de um modelo amplamente adotado na literatura, denominado Beer Game, para avaliar a eficiência local e global dos fornecedores. Para tal, utilizamos perfis distintos baseados em confiança ou em preço. Medimos o impacto de usar tais políticas de seleção no capital acumulado pelos agentes, e concluímos que as parcerias baseadas em confiança são recomendáveis em cenários com ampla disseminação de informações verdadeiras, enquanto que as baseadas em lucro são mais vantajosas em cenários marcados por pouca comunicação ou pelo espalhamento de informações falsas. / Companies in supply chains have the objective of maximizing their productivities, and consequently their profits. A way of to study the behavior of these chains is to simulate them using a multi-agent-based approach. In this work, we added multiple agents at the levels of a widely adopted model in the literature, called Beer Game, to evaluate the local and global performance of suppliers. To do this, we use distinct profiles based on trust or price. We measure the impact of using such selection policies on the agents\' profit, and we could conclude that trust-based partnerships are recommended in scenarios with wide dissemination of true information, while profit-based partnerships are most advantageous in scenarios marked by poor communication or spreading false information.

The computational Grid has become an important infrastructure as an execution environment for scientific applications that require large amount of computing resources. Applications which would otherwise be unmanageable or take a prohibitively longer execution time under previous computing paradigms can now be executed efficiently on the Grid within a reasonable time. Multi-agent based simulation (MABS) is a methodology used to study and understand the dynamics of real world phenomena in domains involving interaction and/or cooperative problem solving where the participants are characterized by entities having autonomous and social behaviour. For certain domains the size of the simulation is extremely large, intractable without employing adequate computing resources such as the Grid. Although the Grid has come with immense opportunities to resource demanding applications such as MABS, it has also brought with it a number of challenges related to performance. Performance problems may have their origins either on the side of the computing infrastructure or the application itself, or both. This thesis aims at improving the performance of MABS applications by overcoming problems inherent to the behaviour of MABS applications. It also studies the extent to which the MABS technologies have been exploited in the field of simulation and find ways to adapt existing technologies for the Grid. It investigates performance monitoring and prediction systems in the Grid environment and their implementation for MABS application with the purpose of identifying application related performance problems and their solutions. Our research shows that large-scale MABS applications have not been implemented despite the fact that many problem domains that cannot be studied properly with only partial simulation. We assume that this is due to the lack of appropriate tools such as MABS platforms for the Grid. Another important finding of this work is the improvement of application performance through the use of MABS specific middleware.

The lack of legitimate datasets on mobile money transactions toperform research on in the domain of fraud detection is a big prob-lem today in the scientic community. Part of the problem is theintrinsic private nature of mobile transactions, not much infor-mation can be exploited. This will leave the researchers with theburden of rst harnessing the dataset before performing the actualresearch on it. The dataset corresponds to the set of data in whichthe research is to be performed on. This thesis discusses a solutionto such a problem, namely the Paysim simulator. Paysim is a -nancial simulator that simulates mobile money transactions basedon an original dataset. We present a solution to ultimately yieldthe possibility to simulate mobile money transactions in such a waythat they become similar to the original dataset. The similarity orthe congruity will be measured by calculating the error-rate betweenthe synthetic data set and the original data set. With technologyframeworks such as "Agent Based" simulation techniques, and theapplication of mathematical statistics, it can be demonstrated thatthe synthetic data is as prudent as the original data set. The aimof this thesis is to demonstrate with statistical models that PaySimcan be used as a tool for the intents of nancial simulations.

This thesis introduces a financial simulation model covering two related financial domains: Mobile Payments and Retail Stores systems.   The problem we address in these domains is different types of fraud. We limit ourselves to isolated cases of relatively straightforward fraud. However, in this thesis the ultimate aim is to introduce our approach towards the use of computer simulation for fraud detection and its applications in financial domains. Fraud is an important problem that impact the whole economy. Currently, there is a lack of public research into the detection of fraud. One important reason is the lack of transaction data which is often sensitive. To address this problem we present a mobile money Payment Simulator (PaySim) and Retail Store Simulator (RetSim), which allow us to generate synthetic transactional data that contains both: normal customer behaviour and fraudulent behaviour.    These simulations are Multi Agent-Based Simulations (MABS) and were calibrated using real data from financial transactions. We developed agents that represent the clients and merchants in PaySim and customers and salesmen in RetSim. The normal behaviour was based on behaviour observed in data from the field, and is codified in the agents as rules of transactions and interaction between clients and merchants, or customers and salesmen. Some of these agents were intentionally designed to act fraudulently, based on observed patterns of real fraud. We introduced known signatures of fraud in our model and simulations to test and evaluate our fraud detection methods. The resulting behaviour of the agents generate a synthetic log of all transactions as a result of the simulation. This synthetic data can be used to further advance fraud detection research, without leaking sensitive information about the underlying data or breaking any non-disclose agreements.   Using statistics and social network analysis (SNA) on real data we calibrated the relations between our agents and generate realistic synthetic data sets that were verified against the domain and validated statistically against the original source.   We then used the simulation tools to model common fraud scenarios to ascertain exactly how effective are fraud techniques such as the simplest form of statistical threshold detection, which is perhaps the most common in use. The preliminary results show that threshold detection is effective enough at keeping fraud losses at a set level. This means that there seems to be little economic room for improved fraud detection techniques.   We also implemented other applications for the simulator tools such as the set up of a triage model and the measure of cost of fraud. This showed to be an important help for managers that aim to prioritise the fraud detection and want to know how much they should invest in fraud to keep the loses below a desired limit according to different experimented and expected scenarios of fraud.

[pt] Simulações de Ambientes Virtuais (VES) são um tipo especial de simulação, normalmente utilizado para implementar jogos ou jogos sérios com representação em espaço virtual e utilizando a técnicas de avanço do tempo de simulação para o próximo evento ou dirigida por tempo. Um exemplo de uso é a aplicação em simulações de apoio a Jogos de Guerra. O uso de Simulações Baseadas em Sistemas Multiagentes (MABS) para implementar VES é adequado devido a possibilidade de modelar e implementar o sistema com ênfase nos atores e seus comportamentos dinâmicos. Contudo, quando os agentes da simulação passam a controlar o avanço do tempo de simulação de forma individualizada, surge uma situação semelhante á simulação paralela, o que implica na necessidade de tratar questões como disputa por recursos computacionais pelos agentes, atrasos em tempo de execução e a perda de consistência da própria simulação. A situação torna-se mais complicada em sistemas desenvolvidos com Java, devido a particularidades desta tecnologia. Este trabalho apresenta uma abordagem para controlar estes atrasos em tempo de execução e assim apoiar o desenvolvimento de VES utilizando MABS com Java. / [en] Virtual Environment Simulations (VES) are a special type of simulation, often used to implement games and serious games with virtual space representation and using both the next-event or stepped–time simulation time advance approach. An example of serious games is the simulation used to support War Games. Multiagent Based Simulation (MABS) are suitable to implement these simulations because of their ability to handle with complexity and individual actors modeling. However, when agents are responsible for advance their own simulation time, a situation similar to a parallel simulation arises. This implies in treat issues such as delays in performing scheduled actions (i.e tardiness) and its consequences in the virtual space representations. This situation is worst in Java based MABS, because of Java technology particularities. This work presents an approach to tame this tardiness and help the development of these cited VES using agent oriented paradigm.

Industries such as trade, manufacturing and transportation have undergone significant changes due to the globalization concept. Sea ports play a very important role in building and strengthening the economies of countries worldwide. Due to the high rate of production, the work load has increased at the ports which resulted into financial as well as capacity problems. As a result of such problems, cost optimized and automated solutions are being developed and introduced at the ports. In the horizontal transport system of the sea ports, AGVs are one of those automated solutions used to transport containers from ships to yard and vice versa. Newer and more practices are being employed to make the efficient transportation of these AGVs. Numexia has recently introduced a new version of Cassette AGVs called Zero-Emission C-AGV. A conceptual model is developed for Zero-Emission C-AGVs and different layouts are evaluated using multi agent-based simulation. The greedy algorithm has been used for the efficient dispatching of jobs. The Simulation will carry out the dispatching of jobs for C-AGVs between quay area and yard using different layouts and scenarios for the unloading operation.

In this thesis we present model of the human work process on projects using multi-agent model. Within the project management plan is carried out comparisons with the fact not only in the context of subsequent checks, but also in the course of the project. One of the most item is cost of human resources. To increase efficiency and control over the actual cost to introducing a range of organizations link the accounting system to a system of reporting work. Such a system registry of the work is not only complex, but also demanding in terms of managing the time gap between the creation of estimates and their own work. In general, there may be several variants of complications such as delay work on the project because of inaccurate estimates of job performance and therefore insufficient funds in the accounts sections and stages of the project. The aim of this work is to find the characteristics of such projects for which this system work. In the first part we are addressed basic theoretical assumptions for modeling work in the field of project management and multi-agent modeling. Next part relates to the creation of multi-agent model, including detailed characteristics and verification. At the end of this research are described a several experiments with the model and analysis results.

In this research we present one of the first actual applications of Multi Agent-Based Simulation (MABS) to the field of software process simulation modelling (SPSM). Although a few previous applications were attempted, we explain in our literature review how these failed to take full advantage of the agency paradigm. Our research resulted in a model of the software development process that integrates performance, cognition and artefact quality, for which we built a common simulation framework to implement and run MABS and System Dynamics (SD) simulators upon the same integrated models. Although it is not possible to fully verify and validate implementations and models like ours, we used a number of verification and validation techniques to increase our confidence in these. Our work is also quite unique in that it compares MABS to SD in the context of SPSM. Here, we uncovered quite interesting properties of each simulation approach and how MABS, for example, is "risk averse" when compared to SD. In our discussion section we also present a number of lessons learned regarding the two simulation paradigms as well as various shortcomings in the models we adopted and our own.